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        <title>IEE Transactions on Medical Imaging via MedWorm.com</title>
        <description>MedWorm.com provides a medical RSS filtering service. Over 6000 RSS medical sources are combined and output via different filters. This feed contains the latest items from the 'IEE Transactions on Medical Imaging' source.</description>
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        <lastBuildDate>Tue, 07 Feb 2012 07:42:48 +0100</lastBuildDate>
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            <title>IEEE Transactions on Medical Imaging information for authors</title>
            <link>http://www.medworm.com/index.php?rid=5657918&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6142692</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Have you visited lately? www.ieee.org</title>
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            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Explore IEL IEEE's most comprehensive resource</title>
            <link>http://www.medworm.com/index.php?rid=5657916&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6142693</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Robust Statistical Fusion of Image Labels</title>
            <link>http://www.medworm.com/index.php?rid=5657915&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6046134</link>
            <description>Image labeling and parcellation (i.e., assigning structure to a collection of voxels) are critical tasks for the assessment of volumetric and morphometric features in medical imaging data. The process of image labeling is inherently error prone as images are corrupted by noise and artifacts. Even expert interpretations are subject to subjectivity and the precision of the individual raters. Hence, all labels must be considered imperfect with some degree of inherent variability. One may seek multiple independent assessments to both reduce this variability and quantify the degree of uncertainty. Existing techniques have exploited maximum a posteriori statistics to combine data from multiple raters and simultaneously estimate rater reliabilities. Although quite successful, wide-scale applicati...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Robustness of Quantitative Compressive Sensing MRI: The Effect of Random Undersampling Patterns on Derived Parameters for DCE- and DSC-MRI</title>
            <link>http://www.medworm.com/index.php?rid=5657914&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6046135</link>
            <description>Compressive sensing (CS) in Cartesian magnetic resonance imaging (MRI) involves random partial Fourier acquisitions. The random nature of these acquisitions can lead to variance in reconstruction errors. In quantitative MRI, variance in the reconstructed images translates to an uncertainty in the derived quantitative maps. We show that for a spatially regularized 2 $times$-accelerated human breast CS DCE-MRI acquisition with a 192$^{2}$ matrix size, the coefficients of variation (CoVs) in voxel-level parameters due to the random acquisition are 1.1%, 0.96%, and 1.5% for the tissue parameters $K^{rm trans}$, $v_{rm e}$, and $v_{rm p}$, with an average error in the mean of $-$2.5%, $-$2.0%, and $-$3.7%, respectively. Only 5% of the acquisition schemes had a systematic underestimation larger ...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Cardiac Motion and Deformation Recovery From MRI: A Review</title>
            <link>http://www.medworm.com/index.php?rid=5657913&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6044719</link>
            <description>Magnetic resonance imaging (MRI) is a highly advanced and sophisticated imaging modality for cardiac motion tracking and analysis, capable of providing 3D analysis of global and regional cardiac function with great accuracy and reproducibility. In the past few years, numerous efforts have been devoted to cardiac motion recovery and deformation analysis from MR image sequences. Many approaches have been proposed for tracking cardiac motion and for computing deformation parameters and mechanical properties of the heart from a variety of cardiac MR imaging techniques. In this paper, an updated and critical review of cardiac motion tracking methods including major references and those proposed in the past ten years is provided. The MR imaging and analysis techniques surveyed are based on cine ...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Supervoxel-Based Segmentation of Mitochondria in EM Image Stacks With Learned Shape Features</title>
            <link>http://www.medworm.com/index.php?rid=5657912&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6044718</link>
            <description>It is becoming increasingly clear that mitochondria play an important role in neural function. Recent studies show mitochondrial morphology to be crucial to cellular physiology and synaptic function and a link between mitochondrial defects and neuro-degenerative diseases is strongly suspected. Electron microscopy (EM), with its very high resolution in all three directions, is one of the key tools to look more closely into these issues but the huge amounts of data it produces make automated analysis necessary. State-of-the-art computer vision algorithms designed to operate on natural 2-D images tend to perform poorly when applied to EM data for a number of reasons. First, the sheer size of a typical EM volume renders most modern segmentation schemes intractable. Furthermore, most approaches...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Fully Automated Attenuation Measurement and Motion Correction in FLIP Image Sequences</title>
            <link>http://www.medworm.com/index.php?rid=5657911&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6043908</link>
            <description>Fluorescence loss in photobleaching (FLIP) is a method to study compartment connectivity in living cells. A FLIP sequence is obtained by alternatively bleaching a spot in a cell and acquiring an image of the complete cell. Connectivity is estimated by comparing fluorescence signal attenuation in different cell parts. The measurements of the fluorescence attenuation are hampered by the low signal to noise ratio of the FLIP sequences, by sudden sample shifts and by sample drift. This paper describes a method that estimates the attenuation by modeling photobleaching as exponentially decaying signals. Sudden motion artifacts are minimized by registering the frames of a FLIP sequence to target frames based on the estimated model and by removing frames that contain deformations. Linear motion (s...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Automated 3-D Segmentation of Lungs With Lung Cancer in CT Data Using a Novel Robust Active Shape Model Approach</title>
            <link>http://www.medworm.com/index.php?rid=5657910&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6042336</link>
            <description>We present a new fully automated approach for segmentation of lungs with such high-density pathologies. Our method consists of two main processing steps. First, a novel robust active shape model (RASM) matching method is utilized to roughly segment the outline of the lungs. The initial position of the RASM is found by means of a rib cage detection method. Second, an optimal surface finding approach is utilized to further adapt the initial segmentation result to the lung. Left and right lungs are segmented individually. An evaluation on 30 data sets with 40 abnormal (lung cancer) and 20 normal left/right lungs resulted in an average Dice coefficient of $0.975pm 0.006$ and a mean absolute surface distance error of $0.84pm 0.23~{hbox {mm}}$, respectively. Experiments on the same 30 data sets ...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Super-Resolution in Respiratory Synchronized Positron Emission Tomography</title>
            <link>http://www.medworm.com/index.php?rid=5657909&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6042337</link>
            <description>In conclusion, the use of SR techniques applied to respiratory motion synchronized images lead to motion compensation combined with improved image SNR and contrast, wi-
hout any increase in the overall acquisition times. (Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Error Analysis of Nonconstant Admittivity for MR-Based Electric Property Imaging</title>
            <link>http://www.medworm.com/index.php?rid=5657908&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6036177</link>
            <description>Magnetic resonance electrical property tomography (MREPT) is a new imaging modality to visualize a distribution of admittivity $gamma=sigma+iomegavarepsilon$ inside the human body where $sigma$ and $varepsilon$ denote electrical conductivity and permittivity, respectively. Using B1 maps acquired by an magnetic resonance imaging scanner, it produces cross-sectional images of $sigma$ and $varepsilon$ at the Larmor frequency. Since current MREPT methods rely on an assumption of a locally homogeneous admittivity, there occurs a reconstruction error where this assumption fails. Rigorously analyzing the reconstruction error in MREPT, we showed that the error is fundamental and may cause technical difficulties in interpreting MREPT images of a general inhomogeneous object. We performed numerical ...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>High Range Resolution Ultrasonographic Vascular Imaging Using Frequency Domain Interferometry With the Capon Method</title>
            <link>http://www.medworm.com/index.php?rid=5657907&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6035979</link>
            <description>For high range resolution ultrasonographic vascular imaging, we apply frequency domain interferometry with the Capon method to a single frame of in-phase and quadrature (IQ) data acquired using a commercial ultrasonographic device with a 7.5 MHz linear array probe. In order to tailor the adaptive beamforming algorithm for ultrasonography we employ four techniques: frequency averaging, whitening, radio-frequency data oversampling, and the moving average. The proposed method had a range resolution of 0.05 mm in an ideal condition, and experimentally detected the boundary couple 0.17 mm apart, where the boundary couple was indistinguishable from a single boundary utilizing a B-mode image. Further, this algorithm could depict a swine femoral artery with a range beam width of 0.054 mm and an es...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Improved Regional Activity Quantitation in Nuclear Medicine Using a New Approach to Correct for Tissue Partial Volume and Spillover Effects</title>
            <link>http://www.medworm.com/index.php?rid=5657906&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6030947</link>
            <description>We have developed a new method of compensating for effects of partial volume and spillover in dual-modality imaging. The approach requires segmentation of just a few tissue types within a small volume-of-interest (VOI) surrounding a lesion; the algorithm estimates simultaneously, from projection data, the activity concentration within each segmented tissue inside the VOI. Measured emission projections were fitted to the sum of resolution-blurred projections of each such tissue, scaled by its unknown activity concentration, plus a global background contribution obtained by reprojection through the reconstructed image volume outside the VOI. The method was evaluated using multiple-pinhole $mu{rm SPECT}$ data simulated for the MOBY mouse phantom containing two spherical lung tumors and one li...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Performance Analysis for Magnetic Resonance Imaging With Nonlinear Encoding Fields</title>
            <link>http://www.medworm.com/index.php?rid=5657905&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6030946</link>
            <description>Nonlinear spatial encoding fields for magnetic resonance imaging (MRI) hold great promise to improve on the linear gradient approaches by, for example, enabling reduced imaging times. Imaging schemes that employ general nonlinear encoding fields are difficult to analyze using traditional measures. In particular, the resolution is spatially varying, characterized by a position-dependent point spread function (PSF). Likewise, the use of nonlinear encoding fields creates an additional spatial dependence on the signal-to-noise ratio (SNR). Although the two properties of resolution and SNR are linked, in this work we focus on the latter. To this end, we examine the pixel variance, which requires a computation that is often not feasible for nonlinear encoding schemes. This paper presents a gener...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Evaluation of Segmentation Algorithms on Cell Populations Using CDF Curves</title>
            <link>http://www.medworm.com/index.php?rid=5657904&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6029989</link>
            <description>Cell segmentation is a critical step in the analysis pipeline for most imaging cytometry experiments and evaluating the performance of segmentation algorithms is important for aiding the selection of segmentation algorithms. Four popular algorithms are evaluated based on their cell segmentation performance. Because segmentation involves the classification of pixels belonging to regions within the cell or belonging to background, these algorithms are evaluated based on their total misclassification error. Misclassification error is particularly relevant in the analysis of quantitative descriptors of cell morphology involving pixel counts, such as projected area, aspect ratio and diameter. Since the cumulative distribution function captures completely the stochastic properties of a populatio...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Medusa: A Scalable MR Console Using USB</title>
            <link>http://www.medworm.com/index.php?rid=5657903&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6029455</link>
            <description>Magnetic resonance imaging (MRI) pulse sequence consoles typically employ closed proprietary hardware, software, and interfaces, making difficult any adaptation for innovative experimental technology. Yet MRI systems research is trending to higher channel count receivers, transmitters, gradient/shims, and unique interfaces for interventional applications. Customized console designs are now feasible for researchers with modern electronic components, but high data rates, synchronization, scalability, and cost present important challenges. Implementing large multichannel MR systems with efficiency and flexibility requires a scalable modular architecture. With Medusa, we propose an open system architecture using the universal serial bus (USB) for scalability, combined with distributed processi...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>A Semi-Markov Model for Mitosis Segmentation in Time-Lapse Phase Contrast Microscopy Image Sequences of Stem Cell Populations</title>
            <link>http://www.medworm.com/index.php?rid=5657902&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6026949</link>
            <description>We propose a semi-Markov model trained in a max-margin learning framework for mitosis event segmentation in large-scale time-lapse phase contrast microscopy image sequences of stem cell populations. Our method consists of three steps. First, we apply a constrained optimization based microscopy image segmentation method that exploits phase contrast optics to extract candidate subsequences in the input image sequence that contains mitosis events. Then, we apply a max-margin hidden conditional random field (MM-HCRF) classifier learned from human-annotated mitotic and nonmitotic sequences to classify each candidate subsequence as a mitosis or not. Finally, a max-margin semi-Markov model (MM-SMM) trained on manually-segmented mitotic sequences is utilized to reinforce the mitosis classification...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Automatic Construction of Parts+Geometry Models for Initializing Groupwise Registration</title>
            <link>http://www.medworm.com/index.php?rid=5657901&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6025299</link>
            <description>Groupwise nonrigid image registration is a powerful tool to automatically establish correspondences across sets of images. Such correspondences are widely used for constructing statistical models of shape and appearance. As existing techniques usually treat registration as an optimization problem, a good initialization is required. Although the standard initialization&amp;#x2014;affine transformation&amp;#x2014;generally works well, it is often inadequate when registering images of complex structures. In this paper we present a more sophisticated method that uses the sparse matches of a parts+geometry model as the initialization. We show that both the model and its matches can be automatically obtained, and that the matches are able to effectively initialize a groupwise nonrigid registration algor...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Incompressible Deformation Estimation Algorithm (IDEA) From Tagged MR Images</title>
            <link>http://www.medworm.com/index.php?rid=5657900&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6022801</link>
            <description>Measuring the 3D motion of muscular tissues, e.g., the heart or the tongue, using magnetic resonance (MR) tagging is typically carried out by interpolating the 2D motion information measured on orthogonal stacks of images. The incompressibility of muscle tissue is an important constraint on the reconstructed motion field and can significantly help to counter the sparsity and incompleteness of the available motion information. Previous methods utilizing this fact produced incompressible motions with limited accuracy. In this paper, we present an incompressible deformation estimation algorithm (IDEA) that reconstructs a dense representation of the 3D displacement field from tagged MR images and the estimated motion field is incompressible to high precision. At each imaged time frame, the tag...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Prior Shape Level Set Segmentation on Multistep Generated Probability Maps of MR Datasets for Fully Automatic Kidney Parenchyma Volumetry</title>
            <link>http://www.medworm.com/index.php?rid=5657899&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6022800</link>
            <description>Fully automatic 3-D segmentation techniques for clinical applications or epidemiological studies have proven to be a very challenging task in the domain of medical image analysis. 3-D organ segmentation on magnetic resonance (MR) datasets requires a well-designed segmentation strategy due to imaging artifacts, partial volume effects, and similar tissue properties of adjacent tissues. We developed a 3-D segmentation framework for fully automatic kidney parenchyma volumetry that uses Bayesian concepts for probability map generation. The probability map quality is improved in a multistep refinement approach. An extended prior shape level set segmentation method is then applied on the refined probability maps. The segmentation quality is improved by incorporating an exterior cortex edge alignm...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Principal Component Based Diffeomorphic Surface Mapping</title>
            <link>http://www.medworm.com/index.php?rid=5657898&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6022802</link>
            <description>We present a new diffeomorphic surface mapping algorithm under the framework of large deformation diffeomorphic metric mapping (LDDMM). Unlike existing LDDMM approaches, this new algorithm reduces the complexity of the estimation of diffeomorphic transformations by incorporating a shape prior in which a nonlinear diffeomorphic shape space is represented by a linear space of initial momenta of diffeomorphic geodesic flows from a fixed template. In addition, for the first time, the diffeomorphic mapping is formulated within a decision-theoretic scheme based on Bayesian modeling in which an empirical shape prior is characterized by a low dimensional Gaussian distribution on initial momentum. This is achieved using principal component analysis (PCA) to construct the eigenspace of the initial m...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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            <title>Reference-Free PRFS MR-Thermometry Using Near-Harmonic 2-D Reconstruction of the Background Phase</title>
            <link>http://www.medworm.com/index.php?rid=5657897&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6021375</link>
            <description>Proton resonance frequency shift (PRFS) MR thermometry (MRT) is the generally preferred method for monitoring thermal ablation, typically implemented with gradient-echo (GRE) sequences. Standard PRFS MRT is based on the subtraction of a temporal reference phase map and is, therefore, intrinsically sensitive to tissue motion (including deformation) and to external perturbation of the magnetic field. Reference-free (or reference-less) PRFS MRT has been previously described by Rieke and was based on a 2-D polynomial fit performed on phase data from outside the heated region, to estimate the background phase inside the region of interest. While their approach was undeniably a fundamental progress in terms of robustness against tissue motion and magnetic perturbations, the underlying mathematic...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Automated Brain Structure Segmentation Based on Atlas Registration and Appearance Models</title>
            <link>http://www.medworm.com/index.php?rid=5657896&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6021414</link>
            <description>Accurate automated brain structure segmentation methods facilitate the analysis of large-scale neuroimaging studies. This work describes a novel method for brain structure segmentation in magnetic resonance images that combines information about a structure's location and appearance. The spatial model is implemented by registering multiple atlas images to the target image and creating a spatial probability map. The structure's appearance is modeled by a classifier based on Gaussian scale-space features. These components are combined with a regularization term in a Bayesian framework that is globally optimized using graph cuts. The incorporation of the appearance model enables the method to segment structures with complex intensity distributions and increases its robustness against errors i...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Generating Super Stimulated-Echoes in MRI and Their Application to Hyperpolarized C-13 Diffusion Metabolic Imaging</title>
            <link>http://www.medworm.com/index.php?rid=5657895&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6058659</link>
            <description>Stimulated-echoes in MR can be used to provide high sensitivity to motion and flow, creating diffusion and perfusion weighting as well as $T_{1}$ contrast, but conventional approaches inherently suffer from a 50% signal loss. The super stimulated-echo, which uses a specialized radio-frequency (RF) pulse train, has been proposed in order to improve the signal while preserving motion and $T_{1}$ sensitivity. This paper presents a novel and straightforward method for designing the super stimulated-echo pulse train using inversion pulse design techniques. This method can also create adiabatic designs with an improved response to RF transmit field variations. The scheme was validated in phantom experiments and shown in vivo to improve signal-to-noise ratio (SNR). We have applied a super stimula...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5657895</comments>
            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Brain Surface Conformal Parameterization With the Ricci Flow</title>
            <link>http://www.medworm.com/index.php?rid=5657894&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6020804</link>
            <description>In brain mapping research, parameterized 3-D surface models are of great interest for statistical comparisons of anatomy, surface-based registration, and signal processing. Here, we introduce the theories of continuous and discrete surface Ricci flow, which can create Riemannian metrics on surfaces with arbitrary topologies with user-defined Gaussian curvatures. The resulting conformal parameterizations have no singularities and they are intrinsic and stable. First, we convert a cortical surface model into a multiple boundary surface by cutting along selected anatomical landmark curves. Secondly, we conformally parameterize each cortical surface to a parameter domain with a user-designed Gaussian curvature arrangement. In the parameter domain, a shape index based on conformal invariants is...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5657894</comments>
            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Automatic Detection and Segmentation of Lymph Nodes From CT Data</title>
            <link>http://www.medworm.com/index.php?rid=5657893&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6033061</link>
            <description>Lymph nodes are assessed routinely in clinical practice and their size is followed throughout radiation or chemotherapy to monitor the effectiveness of cancer treatment. This paper presents a robust learning-based method for automatic detection and segmentation of solid lymph nodes from CT data, with the following contributions. First, it presents a learning based approach to solid lymph node detection that relies on marginal space learning to achieve great speedup with virtually no loss in accuracy. Second, it presents a computationally efficient segmentation method for solid lymph nodes (LN). Third, it introduces two new sets of features that are effective for LN detection, one that self-aligns to high gradients and another set obtained from the segmentation result. The method is evaluat...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5657893</comments>
            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>A Function for Quality Evaluation of Retinal Vessel Segmentations</title>
            <link>http://www.medworm.com/index.php?rid=5657892&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6019055</link>
            <description>Retinal blood vessel assessment plays an important role in the diagnosis of ophthalmic pathologies. The use of digital images for this purpose enables the application of a computerized approach and has fostered the development of multiple methods for automated vascular tree segmentation. Metrics based on contingency tables for binary classification have been widely used for evaluating the performance of these algorithms. Metrics from this family are based on the measurement of a success or failure rate in the detected pixels, obtained by means of pixel-to-pixel comparison between the automated segmentation and a manually-labeled reference image. Therefore, vessel pixels are not considered as a part of a vascular structure with specific features. This paper contributes a function for the ev...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5657892</comments>
            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Fasciculography: Robust Prior-Free Real-Time Normalized Volumetric Neural Tract Parcellation</title>
            <link>http://www.medworm.com/index.php?rid=5657891&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6017127</link>
            <description>Fiber tracking in diffusion tensor magnetic resonance images (DTIs) reveals 3-D structural connectivity of the brain conveniently and thus is a viable tool for investigating neural differences. Unfortunately, local noise, image artifacts and numerical tracking errors during integration-based techniques are cumulative. Prematurely terminated fibers and under-sampled fiber bundles result in incomplete reconstruction of white matter fiber tracts and hence incorrect anatomical measurements. Quantitative cross-subject tract analysis, which is critical for abnormality detection, is complicated by inefficient and inaccurate tract reconstruction and normalization from fiber bundles. Because of the above problems, we propose a parcellation method that aims for lower sensitivity to initialization an...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5657891</comments>
            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>NMF-SVM Based CAD Tool Applied to Functional Brain Images for the Diagnosis of Alzheimer's Disease</title>
            <link>http://www.medworm.com/index.php?rid=5657890&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6017128</link>
            <description>This paper presents a novel computer-aided diagnosis (CAD) technique for the early diagnosis of the Alzheimer's disease (AD) based on nonnegative matrix factorization (NMF) and support vector machines (SVM) with bounds of confidence. The CAD tool is designed for the study and classification of functional brain images. For this purpose, two different brain image databases are selected: a single photon emission computed tomography (SPECT) database and positron emission tomography (PET) images, both of them containing data for both Alzheimer's disease (AD) patients and healthy controls as a reference. These databases are analyzed by applying the Fisher discriminant ratio (FDR) and nonnegative matrix factorization (NMF) for feature selection and extraction of the most relevant features. The re...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5657890</comments>
            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>HRF Estimation in fMRI Data With an Unknown Drift Matrix by Iterative Minimization of the Kullback&amp;#x2013;Leibler Divergence</title>
            <link>http://www.medworm.com/index.php?rid=5657889&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6011702</link>
            <description>Hemodynamic response function (HRF) estimation in noisy functional magnetic resonance imaging (fMRI) plays an important role when investigating the temporal dynamic of a brain region response during activations. Nonparametric methods which allow more flexibility in the estimation by inferring the HRF at each time sample have provided improved performance in comparison to the parametric methods. In this paper, the mixed-effects model is used to derive a new algorithm for nonparametric maximum likelihood HRF estimation. In this model, the random effect is used to better account for the variability of the drift. Contrary to the usual approaches, the proposed algorithm has the benefit of considering an unknown and therefore flexible drift matrix. This allows the effective representation of a b...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5657889</comments>
            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Multi-Channel Microstrip Transceiver Arrays Using Harmonics for High Field MR Imaging in Humans</title>
            <link>http://www.medworm.com/index.php?rid=5657888&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6003790</link>
            <description>Radio-frequency (RF) transceiver array design using primary and higher order harmonics for in vivo parallel magnetic resonance imaging imaging (MRI) and spectroscopic imaging is proposed. The improved electromagnetic decoupling performance, unique magnetic field distributions and high-frequency operation capabilities of higher-order harmonics of resonators would benefit transceiver arrays for parallel MRI, especially for ultrahigh field parallel MRI. To demonstrate this technique, microstrip transceiver arrays using first and second harmonic resonators were developed for human head parallel imaging at 7T. Phantom and human head images were acquired and evaluated using the GRAPPA reconstruction algorithm. The higher-order harmonic transceiver array design technique was also assessed numeric...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5657888</comments>
            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Joint Modeling of Anatomical and Functional Connectivity for Population Studies</title>
            <link>http://www.medworm.com/index.php?rid=5657887&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D5999719</link>
            <description>We propose a novel probabilistic framework to merge information from diffusion weighted imaging tractography and resting-state functional magnetic resonance imaging correlations to identify connectivity patterns in the brain. In particular, we model the interaction between latent anatomical and functional connectivity and present an intuitive extension to population studies. We employ the EM algorithm to estimate the model parameters by maximizing the data likelihood. The method simultaneously infers the templates of latent connectivity for each population and the differences in connectivity between the groups. We demonstrate our method on a schizophrenia study. Our model identifies significant increases in functional connectivity between the parietal/posterior cingulate region and the fro...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5657887</comments>
            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Image Similarity and Tissue Overlaps as Surrogates for Image Registration Accuracy: Widely Used but Unreliable</title>
            <link>http://www.medworm.com/index.php?rid=5657886&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D5977031</link>
            <description>The accuracy of nonrigid image registrations is commonly approximated using surrogate measures such as tissue label overlap scores, image similarity, image difference, or transformation inverse consistency error. This paper provides experimental evidence that these measures, even when used in combination, cannot distinguish accurate from inaccurate registrations. To this end, we introduce a &amp;#x201C;registration&amp;#x201D; algorithm that generates highly inaccurate image transformations, yet performs extremely well in terms of the surrogate measures. Of the tested criteria, only overlap scores of localized anatomical regions reliably distinguish reasonable from inaccurate registrations, whereas image similarity and tissue overlap do not. We conclude that tissue overlap and image similarity, wh...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5657886</comments>
            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>IEEE Transactions on Medical Imaging publication information</title>
            <link>http://www.medworm.com/index.php?rid=5657885&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6142691</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
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            <pubDate>Wed, 01 Feb 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Table of Contents</title>
            <link>http://www.medworm.com/index.php?rid=5657884&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6142636%26arnumber%3D6142690</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <title>Blank page [back cover]</title>
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            <author>IEE Transactions on Medical Imaging</author>
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            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <title>IEEE Transactions on Medical Imaging information for authors</title>
            <link>http://www.medworm.com/index.php?rid=5570439&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6112725%26arnumber%3D6112728</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <title>Scitopia.org</title>
            <link>http://www.medworm.com/index.php?rid=5570438&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6112725%26arnumber%3D6112729</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <title>IEEE Foundation</title>
            <link>http://www.medworm.com/index.php?rid=5570437&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6112725%26arnumber%3D6112730</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Sun, 01 Jan 2012 05:00:00 +0100</pubDate>
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            <title>RERBEE: Robust Efficient Registration via Bifurcations and Elongated Elements Applied to Retinal Fluorescein Angiogram Sequences</title>
            <link>http://www.medworm.com/index.php?rid=5570436&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6112725%26arnumber%3D6015556</link>
            <description>We present RERBEE (robust efficient registration via bifurcations and elongated elements), a novel feature-based registration algorithm able to correct local deformations in high-resolution ultra-wide field-of-view (UWFV) fluorescein angiogram (FA) sequences of the retina. The algorithm is able to cope with peripheral blurring, severe occlusions, presence of retinal pathologies and the change of image content due to the perfusion of the fluorescein dye in time. We have used the computational power of a graphics processor to increase the performance of the most computationally expensive parts of the algorithm by a factor of over $times$ 1300, enabling the algorithm to register a pair of 3900 $times$ 3072 UWFV FA images in 5-10 min instead of the 5&amp;#x2013;7 h required using only the CPU. We ...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Sun, 01 Jan 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Accuracy of Carotid Strain Estimates From Ultrasonic Wall Tracking: A Study Based on Multiphysics Simulations and In Vivo Data</title>
            <link>http://www.medworm.com/index.php?rid=5570435&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6112725%26arnumber%3D5997313</link>
            <description>We used a multiphysics model to assess the accuracy of carotid strain estimates derived from a 1-D ultrasonic wall tracking algorithm. The presented tool integrates fluid-structure interaction (FSI) simulations with an ultrasound simulator (Field II), which allows comparison of the ultrasound (US) images with a ground truth. Field II represents tissue as random points on which US waves reflect and whose position can be updated based on the flow field and vessel wall deformation from FSI. We simulated the RF-signal of a patient-specific carotid bifurcation, including the blood pool as well as the vessel wall and surrounding tissue. Distension estimates were obtained from a wall tracking algorithm using tracking points at various depths within the wall, and further processed to assess radial...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5570435</comments>
            <pubDate>Sun, 01 Jan 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Object Tracking With Particle Filtering in Fluorescence Microscopy Images: Application to the Motion of Neurofilaments in Axons</title>
            <link>http://www.medworm.com/index.php?rid=5570434&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6112725%26arnumber%3D5993543</link>
            <description>Neurofilaments are long flexible cytoplasmic protein polymers that are transported rapidly but intermittently along the axonal processes of nerve cells. Current methods for studying this movement involve manual tracking of fluorescently tagged neurofilament polymers in videos acquired by time-lapse fluorescence microscopy. Here, we describe an automated tracking method that uses particle filtering to implement a recursive Bayesian estimation of the filament location in successive frames of video sequences. To increase the efficiency of this approach, we take advantage of the fact that neurofilament movement is confined within the boundaries of the axon. We use piecewise cubic spline interpolation to model the path of the axon and then we use this model to limit both the orientation and loc...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5570434</comments>
            <pubDate>Sun, 01 Jan 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Robust Student's-t Mixture Model With Spatial Constraints and Its Application in Medical Image Segmentation</title>
            <link>http://www.medworm.com/index.php?rid=5570433&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6112725%26arnumber%3D5989867</link>
            <description>Finite mixture model based on the Student's-t distribution, which is heavily tailed and more robust than Gaussian, has recently received great attention for image segmentation. A new finite Student's-t mixture model (SMM) is proposed in this paper. Existing models do not explicitly incorporate the spatial relationships between pixels. First, our model exploits Dirichlet distribution and Dirichlet law to incorporate the local spatial constrains in an image. Secondly, we directly deal with the Student's-t distribution in order to estimate the model parameters, whereas, the Student's-t distributions in previous models are represented as an infinite mixture of scaled Gaussians that lead to an increase in complexity. Finally, instead of using expectation maximization (EM) algorithm, the propose...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Sun, 01 Jan 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Estimation of Mouse Organ Locations Through Registration of a Statistical Mouse Atlas With Micro-CT Images</title>
            <link>http://www.medworm.com/index.php?rid=5570432&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6112725%26arnumber%3D5989869</link>
            <description>Micro-CT is widely used in preclinical studies of small animals. Due to the low soft-tissue contrast in typical studies, segmentation of soft tissue organs from noncontrast enhanced micro-CT images is a challenging problem. Here, we propose an atlas-based approach for estimating the major organs in mouse micro-CT images. A statistical atlas of major trunk organs was constructed based on 45 training subjects. The statistical shape model technique was used to include inter-subject anatomical variations. The shape correlations between different organs were described using a conditional Gaussian model. For registration, first the high-contrast organs in micro-CT images were registered by fitting the statistical shape model, while the low-contrast organs were subsequently estimated from the hig...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Sun, 01 Jan 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Motion Tracking for Medical Imaging: A Nonvisible Structured Light Tracking Approach</title>
            <link>http://www.medworm.com/index.php?rid=5570431&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6112725%26arnumber%3D5986716</link>
            <description>We present a system for head motion tracking in 3D brain imaging. The system is based on facial surface reconstruction and tracking using a structured light (SL) scanning principle. The system is designed to fit into narrow 3D medical scanner geometries limiting the field of view. It is tested in a clinical setting on the high resolution research tomograph (HRRT), Siemens PET scanner with a head phantom and volunteers. The SL system is compared to a commercial optical tracking system, the Polaris Vicra system, from NDI based on translatory and rotary ground truth motions of the head phantom. The accuracy of the systems was similar, with root mean square (rms) errors of 0.09 $^{circ}$ for $pm 20^{circ}$ axial rotations, and rms errors of 0.24 mm for $pm$ 25 mm translations. Tests were made ...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Sun, 01 Jan 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Texture-Based Analysis of COPD: A Data-Driven Approach</title>
            <link>http://www.medworm.com/index.php?rid=5570430&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6112725%26arnumber%3D5989868</link>
            <description>This study presents a fully automatic, data-driven approach for texture-based quantitative analysis of chronic obstructive pulmonary disease (COPD) in pulmonary computed tomography (CT) images. The approach uses supervised learning where the class labels are, in contrast to previous work, based on measured lung function instead of on manually annotated regions of interest (ROIs). A quantitative measure of COPD is obtained by fusing COPD probabilities computed in ROIs within the lung fields where the individual ROI probabilities are computed using a $k$ nearest neighbor ($k{rm NN}$ ) classifier. The distance between two ROIs in the $k{rm NN}$ classifier is computed as the textural dissimilarity between the ROIs, where the ROI texture is described by histograms of filter responses from a mul...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5570430</comments>
            <pubDate>Sun, 01 Jan 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Generative-Discriminative Basis Learning for Medical Imaging</title>
            <link>http://www.medworm.com/index.php?rid=5570429&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6112725%26arnumber%3D5961630</link>
            <description>This paper presents a novel dimensionality reduction method for classification in medical imaging. The goal is to transform very high-dimensional input (typically, millions of voxels) to a low-dimensional representation (small number of constructed features) that preserves discriminative signal and is clinically interpretable. We formulate the task as a constrained optimization problem that combines generative and discriminative objectives and show how to extend it to the semi-supervised learning (SSL) setting. We propose a novel large-scale algorithm to solve the resulting optimization problem. In the fully supervised case, we demonstrate accuracy rates that are better than or comparable to state-of-the-art algorithms on several datasets while producing a representation of the group diffe...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5570429</comments>
            <pubDate>Sun, 01 Jan 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Medial-Based Deformable Models in Nonconvex Shape-Spaces for Medical Image Segmentation</title>
            <link>http://www.medworm.com/index.php?rid=5570428&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6112725%26arnumber%3D5958610</link>
            <description>We explore the application of genetic algorithms (GA) to deformable models through the proposition of a novel method for medical image segmentation that combines GA with nonconvex, localized, medial-based shape statistics. We replace the more typical gradient descent optimizer used in deformable models with GA, and the convex, implicit, global shape statistics with nonconvex, explicit, localized ones. Specifically, we propose GA to reduce typical deformable model weaknesses pertaining to model initialization, pose estimation and local minima, through the simultaneous evolution of a large number of models. Furthermore, we constrain the evolution, and thus reduce the size of the search-space, by using statistically-based deformable models whose deformations are intuitive (stretch, bulge, ben...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Sun, 01 Jan 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Determination of Axonal and Dendritic Orientation Distributions Within the Developing Cerebral Cortex by Diffusion Tensor Imaging</title>
            <link>http://www.medworm.com/index.php?rid=5570427&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6112725%26arnumber%3D5954184</link>
            <description>As neurons of the developing brain form functional circuits, they undergo morphological differentiation. In immature cerebral cortex, radially-oriented cellular processes of undifferentiated neurons impede water diffusion parallel, but not perpendicular, to the pial surface, as measured via diffusion-weighted magnetic resonance imaging, and give rise to water diffusion anisotropy. As the cerebral cortex matures, the loss of water diffusion anisotropy accompanies cellular morphological differentiation. A quantitative relationship is proposed here to relate water diffusion anisotropy measurements directly to characteristics of neuronal morphology. This expression incorporates the effects of local diffusion anisotropy within cellular processes, as well as the effects of anisotropy in the orie...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Sun, 01 Jan 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Image Processing Assisted Algorithms for Optical Projection Tomography</title>
            <link>http://www.medworm.com/index.php?rid=5570426&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6112725%26arnumber%3D5953523</link>
            <description>Since it was first presented in 2002, optical projection tomography (OPT) has emerged as a powerful tool for the study of biomedical specimen on the mm to cm scale. In this paper, we present computational tools to further improve OPT image acquisition and tomographic reconstruction. More specifically, these methods provide: semi-automatic and precise positioning of a sample at the axis of rotation and a fast and robust algorithm for determination of postalignment values throughout the specimen as compared to existing methods. These tools are easily integrated for use with current commercial OPT scanners and should also be possible to implement in &amp;#x201C;home made&amp;#x201D; or experimental setups for OPT imaging. They generally contribute to increase acquisition speed and quality of OPT data...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Sun, 01 Jan 2012 05:00:00 +0100</pubDate>
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            <title>IEEE Transactions on Medical Imaging publication information</title>
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            <description>(Source: IEE Transactions on Medical Imaging)</description>
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            <pubDate>Sun, 01 Jan 2012 05:00:00 +0100</pubDate>
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        <item>
            <title>Table of Contents</title>
            <link>http://www.medworm.com/index.php?rid=5570424&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6112725%26arnumber%3D6112726</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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        <item>
            <title>Blank page [back cover]</title>
            <link>http://www.medworm.com/index.php?rid=5484733&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6087336%26arnumber%3D6087338</link>
            <description>This page or pages intentionally left blank. (Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
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            <title>IEEE Transactions on Medical Imaging information for authors</title>
            <link>http://www.medworm.com/index.php?rid=5484732&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6087336%26arnumber%3D6087340</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
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            <title>2011 Index IEEE Transactions on Medical Imaging Vol. 30</title>
            <link>http://www.medworm.com/index.php?rid=5484731&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6087336%26arnumber%3D6094271</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
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            <title>IEEE Foundation</title>
            <link>http://www.medworm.com/index.php?rid=5484730&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6087336%26arnumber%3D6087342</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
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            <title>Why we joined</title>
            <link>http://www.medworm.com/index.php?rid=5484729&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6087336%26arnumber%3D6087343</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
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        <item>
            <title>2012 IEEE international conference on image processing</title>
            <link>http://www.medworm.com/index.php?rid=5484728&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6087336%26arnumber%3D6087341</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
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        <item>
            <title>Radial Imaging With Multipolar Magnetic Encoding Fields</title>
            <link>http://www.medworm.com/index.php?rid=5484727&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6087336%26arnumber%3D5981396</link>
            <description>We present reconstruction methods for radial magnetic resonance imaging (MRI) data which were spatially encoded using a pair of orthogonal multipolar magnetic fields for in-plane encoding and parallel imaging. It is shown that a direct method exists in addition to iterative reconstruction. Standard direct projection reconstruction algorithms can be combined with a previously developed direct reconstruction for multipolar encoding fields acquired with Cartesian trajectories. The algorithm is simplified by recasting the reconstruction problem into polar coordinates. In this formulation distortion and aliasing become separate effects. Distortion occurs only along the radial direction and aliasing along the azimuthal direction. Moreover, aliased points are equidistantly distributed in this rep...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
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        <item>
            <title>Accurate and Efficient Optic Disc Detection and Segmentation by a Circular Transformation</title>
            <link>http://www.medworm.com/index.php?rid=5484726&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6087336%26arnumber%3D5981395</link>
            <description>Under the framework of computer-aided diagnosis, this paper presents an accurate and efficient optic disc (OD) detection and segmentation technique. A circular transformation is designed to capture both the circular shape of the OD and the image variation across the OD boundary simultaneously. For each retinal image pixel, it evaluates the image variation along multiple evenly-oriented radial line segments of specific length. The pixels with the maximum variation along all radial line segments are determined, which can be further exploited to locate both the OD center and the OD boundary accurately. Experiments show that OD detection accuracies of 99.75%, 97.5%, and 98.77% are obtained for the STARE dataset, the ARIA dataset, and the MESSIDOR dataset, respectively, and the OD center error ...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
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        <item>
            <title>Self-Stabilizing Colonic Capsule Endoscopy: Pilot Study of Acute Canine Models</title>
            <link>http://www.medworm.com/index.php?rid=5484725&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6087336%26arnumber%3D5963723</link>
            <description>Video capsule endoscopy (VCE) is a noninvasive method for examining the gastrointestinal tract which has been successful in small intestine studies. Recently, VCE has been attempted in the colon. However, the capsule often tumbles in the wider colonic lumen, resulting in missed regions. Self-stabilizing VCE is a novel method to visualize the colon without tumbling. The aim of the present study was to comparatively quantify the effect of stabilization of a commercially available nonmodified capsule endoscope (CE) MiroCam and its modified self-stabilizing version in acute canine experiments. Two customized MiroCam CEs were reduced in volume at the nonimaging back-end to allow the attachment of a self-expanding, biocompatible stabilizing device. Four mongrel dogs underwent laparotomy and exte...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
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        <item>
            <title>Reconstructing the 3D Shape and Bone Mineral Density Distribution of the Proximal Femur From Dual-Energy X-Ray Absorptiometry</title>
            <link>http://www.medworm.com/index.php?rid=5484724&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6087336%26arnumber%3D5962359</link>
            <description>The accurate diagnosis of osteoporosis has gained increasing importance due to the aging of our society. Areal bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DXA) is an established criterion in the diagnosis of osteoporosis. This measure, however, is limited by its two-dimensionality. This work presents a method to reconstruct both the 3D bone shape and 3D BMD distribution of the proximal femur from a single DXA image used in clinical routine. A statistical model of the combined shape and BMD distribution is presented, together with a method for its construction from a set of quantitative computed tomography (QCT) scans. A reconstruction is acquired in an intensity based 3D-2D registration process whereby an instance of the model is found that maximizes the simila...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
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        <item>
            <title>Robust Automatic Knee MR Slice Positioning Through Redundant and Hierarchical Anatomy Detection</title>
            <link>http://www.medworm.com/index.php?rid=5484723&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6087336%26arnumber%3D5959988</link>
            <description>Diagnostic magnetic resonance (MR) image quality is highly dependent on the position and orientation of the slice groups, due to the intrinsic high in-slice and low through-slice resolutions of MR imaging. Hence, the higher speed, accuracy, and reproducibility of automatic slice positioning ,  make it highly desirable over manual slice positioning. However, imaging artifacts, diseases, joint articulation, variations across ages and demographics as well as the extremely high performance requirements prevent state-of-the-art methods, such as volumetric registration, to be an off-the-shelf solution. In this paper, we address all these issues through an automatic slice positioning framework based on redundant and hierarchical learning. Our method has two hallmarks that are specifically designe...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
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            <title>A Combined Manifold Learning Analysis of Shape and Appearance to Characterize Neonatal Brain Development</title>
            <link>http://www.medworm.com/index.php?rid=5484722&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6087336%26arnumber%3D5958609</link>
            <description>Large medical image datasets form a rich source of anatomical descriptions for research into pathology and clinical biomarkers. Many features may be extracted from data such as MR images to provide, through manifold learning methods, new representations of the population's anatomy. However, the ability of any individual feature to fully capture all aspects morphology is limited. We propose a framework for deriving a representation from multiple features or measures which can be chosen to suit the application and are processed using separate manifold-learning steps. The results are then combined to give a single set of embedding coordinates for the data. We illustrate the framework in a population study of neonatal brain MR images and show how consistent representations, correlating well wi...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
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            <title>A Statistical Modeling Approach to the Analysis of Spatial Patterns of FDG-PET Uptake in Human Sarcoma</title>
            <link>http://www.medworm.com/index.php?rid=5484721&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6087336%26arnumber%3D5936120</link>
            <description>Clinical experience with positron emission tomography (PET) scanning of sarcoma, using fluorodeoxyglucose (FDG), has established spatial heterogeneity in the standardized uptake values within the tumor mass as a key prognostic indicator of patient survival. But it may be that a more detailed quantitation of the tumor FDG uptake pattern could provide additional insights into risk. The present work develops a statistical model for this purpose. The approach is based on a tubular representation of the tumor mass with a simplified radial analysis of uptake, transverse to the tubular axis. The technique provides novel ways of characterizing the overall profile of the tumor, including the introduction of an approach for the measurement of its phase of development. The phase measure can distingui...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
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            <title>Tissue-Specific Compartmental Analysis for Dynamic Contrast-Enhanced MR Imaging of Complex Tumors</title>
            <link>http://www.medworm.com/index.php?rid=5484720&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6087336%26arnumber%3D5928416</link>
            <description>Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides a noninvasive method for evaluating tumor vasculature patterns based on contrast accumulation and washout. However, due to limited imaging resolution and tumor tissue heterogeneity, tracer concentrations at many pixels often represent a mixture of more than one distinct compartment. This pixel-wise partial volume effect (PVE) would have profound impact on the accuracy of pharmacokinetics studies using existing compartmental modeling (CM) methods. We, therefore, propose a convex analysis of mixtures (CAM) algorithm to explicitly mitigate PVE by expressing the kinetics in each pixel as a nonnegative combination of underlying compartments and subsequently identifying pure volume pixels at the corners of the clustered pixe...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
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            <title>Cerebral Artery&amp;#x2013;Vein Separation Using 0.1-Hz Oscillation in Dual-Wavelength Optical Imaging</title>
            <link>http://www.medworm.com/index.php?rid=5484719&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6087336%26arnumber%3D5898420</link>
            <description>We present a novel artery&amp;#x2013;vein separation method using 0.1-Hz oscillation at two wavelengths with optical imaging of intrinsic signals (OIS). The 0.1-Hz oscillation at a green light wavelength of 546 nm exhibits greater amplitude in arteries than in veins and is primarily caused by vasomotion, whereas the 0.1-Hz oscillation at a red light wavelength of 630 nm exhibits greater amplitude in veins than in arteries and is primarily caused by changes of deoxyhemoglobin concentration. This spectral feature enables cortical arteries and veins to be segmented independently. The arteries can be segmented on the 0.1-Hz amplitude image at 546 nm using matched filters of a modified dual Gaussian model combining with a single Gaussian model. The veins are a combination of vessels segmented on bo...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Thu, 01 Dec 2011 05:00:00 +0100</pubDate>
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            <title>Identifying Regional Cardiac Abnormalities From Myocardial Strains Using Nontracking-Based Strain Estimation and Spatio-Temporal Tensor Analysis</title>
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            <description>Myocardial strain is a critical indicator of many cardiac diseases and dysfunctions. The goal of this paper is to extract and use the myocardial strain pattern from tagged magnetic resonance imaging (MRI) to identify and localize regional abnormal cardiac function in human subjects. In order to extract the myocardial strains from the tagged images, we developed a novel nontracking-based strain estimation method for tagged MRI. This method is based on the direct extraction of tag deformation, and therefore avoids some limitations of conventional displacement or tracking-based strain estimators. Based on the extracted spatio-temporal strain patterns, we have also developed a novel tensor-based classification framework that better conserves the spatio-temporal structure of the myocardial stra...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <description>(Source: IEE Transactions on Medical Imaging)</description>
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        <item>
            <title>Table of Contents</title>
            <link>http://www.medworm.com/index.php?rid=5484716&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6087336%26arnumber%3D6087337</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
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            <title>Erratum to &amp;#x201C;General Approach to First-Order Error Prediction in Rigid Point Registration&amp;#x201D; [Mar 11 679-693]</title>
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            <description>Presents the revised text for two paragraphs from the above titled paper (ibid., vol. 30, no. 3, pp. 679-693, Mar. 2011). (Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <title>IEEE Transactions on Medical Imaging information for authors</title>
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            <description>(Source: IEE Transactions on Medical Imaging)</description>
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            <title>2012 IEEE membership form</title>
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            <title>Why we joined</title>
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            <description>(Source: IEE Transactions on Medical Imaging)</description>
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            <title>2012 IEEE international conference on image processing</title>
            <link>http://www.medworm.com/index.php?rid=5429371&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6062574%26arnumber%3D6062590</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <title>Erratum to &amp;#x201C;General Approach to First-Order Error Prediction in Rigid Point Registration&amp;#x201D;</title>
            <link>http://www.medworm.com/index.php?rid=5429370&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6062574%26arnumber%3D6062586</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Tue, 01 Nov 2011 04:00:00 +0100</pubDate>
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            <title>Bag-of-Features Based Medical Image Retrieval via Multiple Assignment and Visual Words Weighting</title>
            <link>http://www.medworm.com/index.php?rid=5429369&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6062574%26arnumber%3D5986717</link>
            <description>Bag-of-features based approaches have become prominent for image retrieval and image classification tasks in the past decade. Such methods represent an image as a collection of local features, such as image patches and key points with scale invariant feature transform (SIFT) descriptors. To improve the bag-of-features methods, we first model the assignments of local descriptors as contribution functions, and then propose a novel multiple assignment strategy. Assuming the local features can be reconstructed by their neighboring visual words in a vocabulary, reconstruction weights can be solved by quadratic programming. The weights are then used to build contribution functions, resulting in a novel assignment method, called quadratic programming (QP) assignment. We further propose a novel vi...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Tue, 01 Nov 2011 04:00:00 +0100</pubDate>
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            <title>MR-Guided Thermotherapy of Abdominal Organs Using a Robust PCA-Based Motion Descriptor</title>
            <link>http://www.medworm.com/index.php?rid=5429368&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6062574%26arnumber%3D5936737</link>
            <description>Thermotherapies can now be guided in real-time using magnetic resonance imaging (MRI). This technique is rapidly gaining importance in interventional therapies for abdominal organs such as liver and kidney. An accurate online estimation and characterization of organ displacement is mandatory to prevent misregistration and correct for motion related thermometry artifacts. In addition, when the ablation is performed with an extracorporal heating device such as high intensity focused ultrasound (HIFU), the continuous estimation of the organ displacement is the basis for the dynamic adjustment of the focal point position to track the targeted pathological tissue. In this paper, we describe the use of an optimized principal component analysis (PCA)-based motion descriptor to characterize in rea...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5429368</comments>
            <pubDate>Tue, 01 Nov 2011 04:00:00 +0100</pubDate>
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            <title>Robust Shape Regression for Supervised Vessel Segmentation and its Application to Coronary Segmentation in CTA</title>
            <link>http://www.medworm.com/index.php?rid=5429367&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6062574%26arnumber%3D5929564</link>
            <description>This paper presents a vessel segmentation method which learns the geometry and appearance of vessels in medical images from annotated data and uses this knowledge to segment vessels in unseen images. Vessels are segmented in a coarse-to-fine fashion. First, the vessel boundaries are estimated with multivariate linear regression using image intensities sampled in a region of interest around an initialization curve. Subsequently, the position of the vessel boundary is refined with a robust nonlinear regression technique using intensity profiles sampled across the boundary of the rough segmentation and using information about plausible cross-sectional vessel shapes. The method was evaluated by quantitatively comparing segmentation results to manual annotations of 229 coronary arteries. On ave...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Tue, 01 Nov 2011 04:00:00 +0100</pubDate>
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            <title>Common-Mode Differential-Mode (CMDM) Method for Double-Nuclear MR Signal Excitation and Reception at Ultrahigh Fields</title>
            <link>http://www.medworm.com/index.php?rid=5429366&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6062574%26arnumber%3D5898421</link>
            <description>Double-tuned radio-frequency (RF) coils for heteronuclear mangentic resonance (MR) require sufficient electromagnetic isolation between the two resonators operating at two Larmor frequencies and independent tuning in order to attain highly efficient signal acquisition at each frequency. In this work, a novel method for double-tuned coil design at 7T based on the concept of common-mode differential-mode (CMDM) was developed and tested. Common mode (CM) and differential mode (DM) currents exist within two coupled parallel transmission lines, e.g., microstrip lines, yielding two different current distributions. The electromagnetic (EM) fields of the CM and DM are orthogonal to each other, and thus, the two modes are intrinsically EM decoupled. The modes can be tuned independently to desired f...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5429366</comments>
            <pubDate>Tue, 01 Nov 2011 04:00:00 +0100</pubDate>
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            <title>The Singular Value Filter: A General Filter Design Strategy for PCA-Based Signal Separation in Medical Ultrasound Imaging</title>
            <link>http://www.medworm.com/index.php?rid=5429365&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6062574%26arnumber%3D5898419</link>
            <description>A general filtering method, called the singular value filter (SVF), is presented as a framework for principal component analysis (PCA) based filter design in medical ultrasound imaging. The SVF approach operates by projecting the original data onto a new set of bases determined from PCA using singular value decomposition (SVD). The shape of the SVF weighting function, which relates the singular value spectrum of the input data to the filtering coefficients assigned to each basis function, is designed in accordance with a signal model and statistical assumptions regarding the underlying source signals. In this paper, we applied SVF for the specific application of clutter artifact rejection in diagnostic ultrasound imaging. SVF was compared to a conventional PCA-based filtering technique, wh...</description>
            <author>IEE Transactions on Medical Imaging</author>
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        <comments>http://www.medworm.com/rss/comments.php?id=5429365</comments>
            <pubDate>Tue, 01 Nov 2011 04:00:00 +0100</pubDate>
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            <title>Automated Measurement of the Arteriolar-to-Venular Width Ratio in Digital Color Fundus Photographs</title>
            <link>http://www.medworm.com/index.php?rid=5429364&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6062574%26arnumber%3D5876322</link>
            <description>A decreased ratio of the width of retinal arteries to veins [arteriolar-to-venular diameter ratio (AVR)], is well established as predictive of cerebral atrophy, stroke and other cardiovascular events in adults. Tortuous and dilated arteries and veins, as well as decreased AVR are also markers for plus disease in retinopathy of prematurity. This work presents an automated method to estimate the AVR in retinal color images by detecting the location of the optic disc, determining an appropriate region of interest (ROI), classifying vessels as arteries or veins, estimating vessel widths, and calculating the AVR. After vessel segmentation and vessel width determination, the optic disc is located and the system eliminates all vessels outside the AVR measurement ROI. A skeletonization operation i...</description>
            <author>IEE Transactions on Medical Imaging</author>
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        <comments>http://www.medworm.com/rss/comments.php?id=5429364</comments>
            <pubDate>Tue, 01 Nov 2011 04:00:00 +0100</pubDate>
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            <title>Motion-Induced Phase Error Estimation and Correction in 3D Diffusion Tensor Imaging</title>
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            <description>A multishot data acquisition strategy is one way to mitigate B0 distortion and ${rm T}2ast$ blurring for high-resolution diffusion-weighted magnetic resonance imaging experiments. However, different object motions that take place during different shots cause phase inconsistencies in the data, leading to significant image artifacts. This work proposes a maximum likelihood estimation and $k$-space correction of motion-induced phase errors in 3D multishot diffusion tensor imaging. The proposed error estimation is robust, unbiased, and approaches the Cramer&amp;#x2013;Rao lower bound. For rigid body motion, the proposed correction effectively removes motion-induced phase errors regardless of the $k$-space trajectory used and gives comparable performance to the more computationally expensive 3D ite...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Tue, 01 Nov 2011 04:00:00 +0100</pubDate>
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            <title>Prediction Based Collaborative Trackers (PCT): A Robust and Accurate Approach Toward 3D Medical Object Tracking</title>
            <link>http://www.medworm.com/index.php?rid=5429362&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6062574%26arnumber%3D5783346</link>
            <description>Robust and fast 3D tracking of deformable objects, such as heart, is a challenging task because of the relatively low image contrast and speed requirement. Many existing 2D algorithms might not be directly applied on the 3D tracking problem. The 3D tracking performance is limited due to dramatically increased data size, landmarks ambiguity, signal drop-out or complex nonrigid deformation. In this paper, we present a robust, fast, and accurate 3D tracking algorithm: prediction based collaborative trackers (PCT). A novel one-step forward prediction is introduced to generate the motion prior using motion manifold learning. Collaborative trackers are introduced to achieve both temporal consistency and failure recovery. Compared with tracking by detection and 3D optical flow, PCT provides the b...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Tue, 01 Nov 2011 04:00:00 +0100</pubDate>
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            <title>Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge</title>
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            <description>EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010) is a public platform for fair and meaningful comparison of registration algorithms which are applied to a database of intrapatient thoracic CT image pairs. Evaluation of nonrigid registration techniques is a nontrivial task. This is compounded by the fact that researchers typically test only on their own data, which varies widely. For this reason, reliable assessment and comparison of different registration algorithms has been virtually impossible in the past. In this work we present the results of the launch phase of EMPIRE10, which comprised the comprehensive evaluation and comparison of 20 individual algorithms from leading academic and industrial research groups. All algorithms are applied to the same set of 30 thor...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Tue, 01 Nov 2011 04:00:00 +0100</pubDate>
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            <title>Modelling Prostate Motion for Data Fusion During Image-Guided Interventions</title>
            <link>http://www.medworm.com/index.php?rid=5429360&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6062574%26arnumber%3D5782991</link>
            <description>There is growing clinical demand for image registration techniques that allow multimodal data fusion for accurate targeting of needle biopsy and ablative prostate cancer treatments. However, during procedures where transrectal ultrasound (TRUS) guidance is used, substantial gland deformation can occur due to TRUS probe pressure. In this paper, the ability of a statistical shape/motion model, trained using finite element simulations, to predict and compensate for this source of motion is investigated. Three-dimensional ultrasound images acquired on five patient prostates, before and after TRUS-probe-induced deformation, were registered using a nonrigid, surface-based method, and the accuracy of different deformation models compared. Registration using a statistical motion model was found to...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Tue, 01 Nov 2011 04:00:00 +0100</pubDate>
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            <title>A Reproducing Kernel Hilbert Space Approach for Q-Ball Imaging</title>
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            <description>This article proposes to employ the Funk&amp;#x2013;Radon transform in a Hilbert space with a reproducing kernel derived from the spherical Laplace&amp;#x2013;Beltrami operator, thus generalizing previous approaches that assume a bandlimited diffusion signal. The function estimation problem is solved within a Tikhonov regularization framework, while a Gaussian process model allows for the selection of the smoothing parameter and the specification of confidence bands. Shortcomings of Q-ball imaging are discussed. (Source: IEE Transactions on Medical Imaging)</description>
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            <title>IEEE Transactions on Medical Imaging publication information</title>
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            <title>Table of Contents</title>
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            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
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        <item>
            <title>IEEE Transactions on Medical Imaging information for authors</title>
            <link>http://www.medworm.com/index.php?rid=5271097&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6031185%26arnumber%3D6031187</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
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        <item>
            <title>Automatic Aneurysm Neck Detection Using Surface Voronoi Diagrams</title>
            <link>http://www.medworm.com/index.php?rid=5271096&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6031185%26arnumber%3D5773494</link>
            <description>A new automatic approach for saccular intracranial aneurysm isolation is proposed in this work. Due to the inter- and intra-observer variability in manual delineation of the aneurysm neck, a definition based on a minimum cost path around the aneurysm sac is proposed that copes with this variability and is able to make consistent measurements along different data sets, as well as to automate and speedup the analysis of cerebral aneurysms. The method is based on the computation of a minimal path along a scalar field obtained on the vessel surface, to find the aneurysm neck in a robust and fast manner. The computation of the scalar field on the surface is obtained using a fast marching approach with a speed function based on the exponential of the distance from the centerline bifurcation betw...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
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        <item>
            <title>A Supervised Patch-Based Approach for Human Brain Labeling</title>
            <link>http://www.medworm.com/index.php?rid=5271095&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6031185%26arnumber%3D5771116</link>
            <description>We propose in this work a patch-based image labeling method relying on a label propagation framework. Based on image intensity similarities between the input image and an anatomy textbook, an original strategy which does not require any nonrigid registration is presented. Following recent developments in nonlocal image denoising, the similarity between images is represented by a weighted graph computed from an intensity-based distance between patches. Experiments on simulated and in vivo magnetic resonance images show that the proposed method is very successful in providing automated human brain labeling. (Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
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        <item>
            <title>An Anatomically Oriented Breast Coordinate System for Mammogram Analysis</title>
            <link>http://www.medworm.com/index.php?rid=5271094&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6031185%26arnumber%3D5772932</link>
            <description>We have developed a breast coordinate system that is based on breast anatomy to register female breasts into a common coordinate frame in 2-D mediolateral (ML) or mediolateral oblique (MLO) view mammograms. The breasts are registered according to the location of the pectoral muscle and the nipple and the shape of the breast boundary because these are the most robust features independent of the breast size and shape. On the basis of these landmarks, we have constructed a nonlinear mapping between the parameter frame and the breast region in the mammogram. This mapping makes it possible to identify the corresponding positions and orientations among all of the ML or MLO mammograms, which facilitates an implicit use of the registration, i.e., no explicit image warping is needed. We additionall...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5271094</comments>
            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
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        <item>
            <title>PopTract: Population-Based Tractography</title>
            <link>http://www.medworm.com/index.php?rid=5271093&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6031185%26arnumber%3D5766754</link>
            <description>White matter fiber tractography plays a key role in the in vivo understanding of brain circuitry. For tract-based comparison of a population of images, a common approach is to first generate an atlas by averaging, after spatial normalization, all images in the population, and then perform tractography using the constructed atlas. The reconstructed fiber trajectories form a common geometry onto which diffusion properties of each individual subject can be projected based on the corresponding locations in the subject native space. However, in the case of high angular resolution diffusion imaging (HARDI), where modeling fiber crossings is an important goal, the above-mentioned averaging method for generating an atlas results in significant error in the estimation of local fiber orientations an...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5271093</comments>
            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
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        <item>
            <title>A Nonrigid Registration Framework Using Spatially Encoded Mutual Information and Free-Form Deformations</title>
            <link>http://www.medworm.com/index.php?rid=5271092&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6031185%26arnumber%3D5762609</link>
            <description>Mutual information (MI) registration including spatial information has been shown to perform better than the traditional MI measures for certain nonrigid registration tasks. In this work, we first provide new insight to problems of the MI-based registration and propose to use the spatially encoded mutual information (SEMI) to tackle these problems. To encode spatial information, we propose a hierarchical weighting scheme to differentiate the contribution of sample points to a set of entropy measures, which are associated to spatial variable values. By using free-form deformations (FFDs) as the transformation model, we can first define the spatial variable using the set of FFD control points, and then propose a local ascent optimization scheme for nonrigid SEMI registration. The proposed SE...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5271092</comments>
            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
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        <item>
            <title>Optimal Rebinning of Time-of-Flight PET Data</title>
            <link>http://www.medworm.com/index.php?rid=5271091&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6031185%26arnumber%3D5762352</link>
            <description>Time-of-flight (TOF) positron emission tomography (PET) scanners offer the potential for significantly improved signal-to-noise ratio (SNR) and lesion detectability in clinical PET. However, fully 3D TOF PET image reconstruction is a challenging task due to the huge data size. One solution to this problem is to rebin TOF data into a lower dimensional format. We have recently developed Fourier rebinning methods for mapping TOF data into non-TOF formats that retain substantial SNR advantages relative to sinograms acquired without TOF information. However, mappings for rebinning into non-TOF formats are not unique and optimization of rebinning methods has not been widely investigated. In this paper we address the question of optimal rebinning in order to make full use of TOF information. We f...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5271091</comments>
            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
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        <item>
            <title>Multi-Pinhole SPECT Calibration: Influence of Data Noise and Systematic Orbit Deviations</title>
            <link>http://www.medworm.com/index.php?rid=5271090&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6031185%26arnumber%3D5756692</link>
            <description>The geometry of a single pinhole SPECT system with circular orbit can be uniquely determined from a measurement of three point sources, provided that at least two inter-point distances are known. In contrast, it has been shown mathematically that, for a multi-pinhole SPECT system with circular orbit, only two point sources are needed, and the knowledge of the distance between them is not required. In this paper, we report that this conclusion only holds if the motion of the camera is perfectly circular. In reality, the detector heads systematically slightly deviate from the circular orbit, which may introduce non-negligible bias in the estimated parameters and degrade the reconstructed image. An analytical linear model was extended to estimate the influence of both data noise and systemati...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5271090</comments>
            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
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        <item>
            <title>Robust Statistical Label Fusion Through Consensus Level, Labeler Accuracy, and Truth Estimation (COLLATE)</title>
            <link>http://www.medworm.com/index.php?rid=5271089&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6031185%26arnumber%3D5756482</link>
            <description>Segmentation and delineation of structures of interest in medical images is paramount to quantifying and characterizing structural, morphological, and functional correlations with clinically relevant conditions. The established gold standard for performing segmentation has been manual voxel-by-voxel labeling by a neuroanatomist expert. This process can be extremely time consuming, resource intensive and fraught with high inter-observer variability. Hence, studies involving characterizations of novel structures or appearances have been limited in scope (numbers of subjects), scale (extent of regions assessed), and statistical power. Statistical methods to fuse data sets from several different sources (e.g., multiple human observers) have been proposed to simultaneously estimate both rater p...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5271089</comments>
            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
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        <item>
            <title>Magnetic Resonance Electrical Impedance Tomography for Monitoring Electric Field Distribution During Tissue Electroporation</title>
            <link>http://www.medworm.com/index.php?rid=5271088&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6031185%26arnumber%3D5756240</link>
            <description>Electroporation is a phenomenon caused by externally applied electric field of an adequate strength and duration to cells that results in the increase of cell membrane permeability to various molecules, which otherwise are deprived of transport mechanism. As accurate coverage of the tissue with a sufficiently large electric field presents one of the most important conditions for successful electroporation, applications based on electroporation would greatly benefit with a method of monitoring the electric field, especially if it could be done during the treatment. As the membrane electroporation is a consequence of an induced transmembrane potential which is directly proportional to the local electric field, we propose current density imaging (CDI) and magnetic resonance electrical impedan...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5271088</comments>
            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5271088</guid>        </item>
        <item>
            <title>Topology-Based Kernels With Application to Inference Problems in Alzheimer's Disease</title>
            <link>http://www.medworm.com/index.php?rid=5271087&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6031185%26arnumber%3D5756483</link>
            <description>Alzheimer's disease (AD) research has recently witnessed a great deal of activity focused on developing new statistical learning tools for automated inference using imaging data. The workhorse for many of these techniques is the support vector machine (SVM) framework (or more generally kernel-based methods). Most of these require, as a first step, specification of a kernel matrix ${cal K}$ between input examples (i.e., images). The inner product between images $I_{i}$ and $I_{j}$ in a feature space can generally be written in closed form and so it is convenient to treat ${cal K}$ as &amp;#x201C;given.&amp;#x201D; However, in certain neuroimaging applications such an assumption becomes problematic. As an example, it is rather challenging to provide a scalar measure of similarity between two instanc...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5271087</comments>
            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5271087</guid>        </item>
        <item>
            <title>Simultaneous Multi-scale Registration Using Large Deformation Diffeomorphic Metric Mapping</title>
            <link>http://www.medworm.com/index.php?rid=5271086&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6031185%26arnumber%3D5755203</link>
            <description>In the framework of large deformation diffeomorphic metric mapping (LDDMM), we present a practical methodology to integrate prior knowledge about the registered shapes in the regularizing metric. Our goal is to perform rich anatomical shape comparisons from volumetric images with the mathematical properties offered by the LDDMM framework. We first present the notion of characteristic scale at which image features are deformed. We then propose a methodology to compare anatomical shape variations in a multi-scale fashion, i.e., at several characteristic scales simultaneously. In this context, we propose a strategy to quantitatively measure the feature differences observed at each characteristic scale separately. After describing our methodology, we illustrate the performance of the method on...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5271086</comments>
            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
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        <item>
            <title>Automatic Nonrigid Calibration of Image Registration for Real Time MR-Guided HIFU Ablations of Mobile Organs</title>
            <link>http://www.medworm.com/index.php?rid=5271085&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6031185%26arnumber%3D5762608</link>
            <description>Real time magnetic resonance imaging (MRI) is rapidly gaining importance in interventional therapies. An accurate motion estimation is required for mobile targets and can be conveniently addressed using an image registration algorithm. Since the adaptation of the control parameters of the algorithm depends on the application (targeted organ, location of the tumor, slice orientation, etc.), typically an individual calibration is required. However, the assessment of the estimated motion accuracy is difficult since the real target motion is unknown. In this paper, existing criteria based only on anatomical image similarity are demonstrated to be inadequate. A new criterion is introduced, which is based on the local magnetic field distribution. The proposed criterion was used to assess, during...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5271085</comments>
            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
            <guid isPermaLink="false">5271085</guid>        </item>
        <item>
            <title>Frequency-Domain Optical Tomographic Imaging of Arthritic Finger Joints</title>
            <link>http://www.medworm.com/index.php?rid=5271084&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6031185%26arnumber%3D5741853</link>
            <description>We are presenting data from the largest clinical trial on optical tomographic imaging of finger joints to date. Overall we evaluated 99 fingers of patients affected by rheumatoid arthritis (RA) and 120 fingers from healthy volunteers. Using frequency-domain imaging techniques we show that sensitivities and specificities of 0.85 and higher can be achieved in detecting RA. This is accomplished by deriving multiple optical parameters from the optical tomographic images and combining them for the statistical analysis. Parameters derived from the scattering coefficient perform slightly better than absorption derived parameters. Furthermore we found that data obtained at 600 MHz leads to better classification results than data obtained at 0 or 300 MHz. (Source: IEE Transactions on Medical Imagin...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5271084</comments>
            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
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        <item>
            <title>IEEE Transactions on Medical Imaging publication information</title>
            <link>http://www.medworm.com/index.php?rid=5271083&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6031185%26arnumber%3D6031189</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
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        <item>
            <title>Table of Contents</title>
            <link>http://www.medworm.com/index.php?rid=5271082&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6031185%26arnumber%3D6031186</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Sat, 01 Oct 2011 04:00:00 +0100</pubDate>
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        <item>
            <title>Blank page</title>
            <link>http://www.medworm.com/index.php?rid=5181113&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6006638%26arnumber%3D6006651</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Wed, 31 Aug 2011 23:00:00 +0100</pubDate>
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            <title>IEEE Transactions on Medical Imaging information for authors</title>
            <link>http://www.medworm.com/index.php?rid=5181112&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6006638%26arnumber%3D6006652</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5181112</comments>
            <pubDate>Wed, 31 Aug 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>2011 IEEE membership form</title>
            <link>http://www.medworm.com/index.php?rid=5181111&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6006638%26arnumber%3D6006639</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5181111</comments>
            <pubDate>Wed, 31 Aug 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>Special issue on medical imaging in computational physiology</title>
            <link>http://www.medworm.com/index.php?rid=5181110&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6006638%26arnumber%3D6006649</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5181110</comments>
            <pubDate>Wed, 31 Aug 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>A Reduced Order Explicit Dynamic Finite Element Algorithm for Surgical Simulation</title>
            <link>http://www.medworm.com/index.php?rid=5181109&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6006638%26arnumber%3D5752246</link>
            <description>We present an explicit finite element scheme in which time integration is performed in a reduced basis. Futhermore, we present a simple procedure for imposing inhomogeneous essential boundary conditions, thus overcoming one of the principal deficiencies of such approaches. The computational benefits of the procedure within a GPU-based execution framework are examined, and an assessment of the errors introduced is given. It is shown that speedups approaching an order of magnitude are feasible, without introduction of prohibitive errors, and without hardware modifications. The procedure may have applications in interactive simulation and medical image-guidance problems, in which both speed and accuracy are vital. (Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5181109</comments>
            <pubDate>Wed, 31 Aug 2011 23:00:00 +0100</pubDate>
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            <title>Bias Field Inconsistency Correction of Motion-Scattered Multislice MRI for Improved 3D Image Reconstruction</title>
            <link>http://www.medworm.com/index.php?rid=5181108&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6006638%26arnumber%3D5752245</link>
            <description>A common solution to clinical MR imaging in the presence of large anatomical motion is to use fast multislice 2D studies to reduce slice acquisition time and provide clinically usable slice data. Recently, techniques have been developed which retrospectively correct large scale 3D motion between individual slices allowing the formation of a geometrically correct 3D volume from the multiple slice stacks. One challenge, however, in the final reconstruction process is the possibility of varying intensity bias in the slice data, typically due to the motion of the anatomy relative to imaging coils. As a result, slices which cover the same region of anatomy at different times may exhibit different sensitivity. This bias field inconsistency can induce artifacts in the final 3D reconstruction that...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5181108</comments>
            <pubDate>Wed, 31 Aug 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>BOLD Contrast and Noise Characteristics of Densely Sampled Multi-Echo fMRI Data</title>
            <link>http://www.medworm.com/index.php?rid=5181107&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6006638%26arnumber%3D5751699</link>
            <description>Blood oxygenation level dependent (BOLD) contrast in functional magnetic resonance imaging (fMRI) can be enhanced using multi-echo imaging and postprocessing techniques that combine the echoes in weighted summation. Here, existing echo-weighting methods are reassessed in the context of an explicit physiological noise model, and a new method is introduced: weights that scale linearly with echo time. Additionally, a method using data-driven weights defined using principal component analysis (PCA) is included for comparison. Differences in BOLD contrast enhancement between methods were compared analytically where possible, and using Monte Carlo simulations for different noise conditions and different combinations of acquisition parameters. The comparisons were also validated through densely s...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5181107</comments>
            <pubDate>Wed, 31 Aug 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>Sensitivity of Photon-Counting Based  ${rm K}$-Edge Imaging in X-ray Computed Tomography</title>
            <link>http://www.medworm.com/index.php?rid=5181106&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6006638%26arnumber%3D5749698</link>
            <description>The feasibility of ${rm K}$-edge imaging using energy-resolved, photon-counting transmission measurements in X-ray computed tomography (CT) has been demonstrated by simulations and experiments. The method is based on probing the discontinuities of the attenuation coefficient of heavy elements above and below the ${rm K}$-edge energy by using energy-sensitive, photon counting X-ray detectors. In this paper, we investigate the dependence of the sensitivity of ${rm K}$-edge imaging on the atomic number ${ Z}$ of the contrast material, on the object diameter ${ D}$ , on the spectral response of the X-ray detector and on the X-ray tube voltage. We assume a photon-counting detector equipped with six adjustable energy thresholds. Physical effects leading to a degradation of the energy resolution ...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Wed, 31 Aug 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>Partitioning Histopathological Images: An Integrated Framework for Supervised Color-Texture Segmentation and Cell Splitting</title>
            <link>http://www.medworm.com/index.php?rid=5181105&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6006638%26arnumber%3D5746646</link>
            <description>For quantitative analysis of histopathological images, such as the lymphoma grading systems, quantification of features is usually carried out on single cells before categorizing them by classification algorithms. To this end, we propose an integrated framework consisting of a novel supervised cell-image segmentation algorithm and a new touching-cell splitting method. For the segmentation part, we segment the cell regions from the other areas by classifying the image pixels into either cell or extra-cellular category. Instead of using pixel color intensities, the color-texture extracted at the local neighborhood of each pixel is utilized as the input to our classification algorithm. The color-texture at each pixel is extracted by local Fourier transform (LFT) from a new color space, the mo...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5181105</comments>
            <pubDate>Wed, 31 Aug 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>A Fast Wavelet-Based Reconstruction Method for Magnetic Resonance Imaging</title>
            <link>http://www.medworm.com/index.php?rid=5181104&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6006638%26arnumber%3D5744123</link>
            <description>We present a mathematical analysis that explains the performance of the algorithms. Using simulated and in vivo data, we show that our nonlinear method is fast, as it accelerates ISTA by almost two orders of magnitude. We also show that it remains competitive with TV regularization in terms of image quality. (Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Wed, 31 Aug 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>Structural Analysis of Articular Cartilage Using Multiphoton Microscopy: Input for Biomechanical Modeling</title>
            <link>http://www.medworm.com/index.php?rid=5181103&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6006638%26arnumber%3D5744126</link>
            <description>The 3-D morphology of chicken articular cartilage was quantified using multiphoton microscopy (MPM) for use in continuum-mechanical modeling. To motivate this morphological study we propose aspects of a new, 3-D finite strain constitutive model for articular cartilage focusing on the essential load-bearing morphology: an inhomogeneous, poro-(visco)elastic solid matrix reinforced by an anisotropic, (visco)elastic dispersed fiber fabric which is saturated by an incompressible fluid residing in strain-dependent pores. Samples of fresh chicken cartilage were sectioned in three orthogonal planes and imaged using MPM, specifically imaging the collagen fibers using second harmonic generation. Employing image analysis techniques based on Fourier analysis, we derived the principal directionality an...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5181103</comments>
            <pubDate>Wed, 31 Aug 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>Robust Brain Extraction Across Datasets and Comparison With Publicly Available Methods</title>
            <link>http://www.medworm.com/index.php?rid=5181102&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6006638%26arnumber%3D5742706</link>
            <description>Automatic whole-brain extraction from magnetic resonance images (MRI), also known as skull stripping, is a key component in most neuroimage pipelines. As the first element in the chain, its robustness is critical for the overall performance of the system. Many skull stripping methods have been proposed, but the problem is not considered to be completely solved yet. Many systems in the literature have good performance on certain datasets (mostly the datasets they were trained/tuned on), but fail to produce satisfactory results when the acquisition conditions or study populations are different. In this paper we introduce a robust, learning-based brain extraction system (ROBEX). The method combines a discriminative and a generative model to achieve the final result. The discriminative model i...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5181102</comments>
            <pubDate>Wed, 31 Aug 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>A Statistical Model for Quantification and Prediction of Cardiac Remodelling: Application to Tetralogy of Fallot</title>
            <link>http://www.medworm.com/index.php?rid=5181101&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6006638%26arnumber%3D5741734</link>
            <description>This study aims to quantify the regional impacts of valve regurgitation and heart growth upon the end-diastolic right ventricle (RV) in patients with tetralogy of Fallot, a severe congenital heart defect. The ultimate goal is to determine, among clinical variables, predictors for the RV shape from which a statistical model that predicts RV remodelling is built. Our approach relies on a forward model based on currents and a diffeomorphic surface registration algorithm to estimate an unbiased template. Local effects of RV regurgitation upon the RV shape were assessed with Principal Component Analysis (PCA) and cross-sectional multivariate design. A generative 3-D model of RV growth was then estimated using partial least squares (PLS) and canonical correlation analysis (CCA). Applied on a ret...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5181101</comments>
            <pubDate>Wed, 31 Aug 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>Unmixing Dynamic Fluorescence Diffuse Optical Tomography Images With Independent Component Analysis</title>
            <link>http://www.medworm.com/index.php?rid=5181100&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6006638%26arnumber%3D5779741</link>
            <description>Dynamic fluorescence diffuse optical tomography (D-FDOT) is important for drug delivery research. However, the low spatial resolution of FDOT and the complex kinetics of drug limit the ability of D-FDOT in resolving metabolic processes of drug throughout whole body of small animals. In this paper, we propose an independent component analysis (ICA)-based method to perform D-FDOT studies. When applied to D-FDOT images, ICA not only generates a set of independent components (ICs) which can illustrate functional structures with different kinetic behaviors, but also provides a set of associated time courses (TCs) which can represent normalized time courses of drug in corresponding functional structures. Further, the drug concentration in specific functional structure at different time points ca...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5181100</comments>
            <pubDate>Wed, 31 Aug 2011 23:00:00 +0100</pubDate>
            <guid isPermaLink="false">5181100</guid>        </item>
        <item>
            <title>Multidimensional X-Space Magnetic Particle Imaging</title>
            <link>http://www.medworm.com/index.php?rid=5181099&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6006638%26arnumber%3D5728922</link>
            <description>Magnetic particle imaging (MPI) is a promising new medical imaging tracer modality with potential applications in human angiography, cancer imaging, in vivo cell tracking, and inflammation imaging. Here we demonstrate both theoretically and experimentally that multidimensional MPI is a linear shift-invariant imaging system with an analytic point spread function. We also introduce a fast image reconstruction method that obtains the intrinsic MPI image with high signal-to-noise ratio via a simple gridding operation in x-space. We also demonstrate a method to reconstruct large field-of-view (FOV) images using partial FOV scanning, despite the loss of first harmonic image information due to direct feedthrough contamination. We conclude with the first experimental test of multidimensional x-spa...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=5181099</comments>
            <pubDate>Wed, 31 Aug 2011 23:00:00 +0100</pubDate>
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            <title>IEEE Transactions on Medical Imaging publication information</title>
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            <description>(Source: IEE Transactions on Medical Imaging)</description>
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            <pubDate>Wed, 31 Aug 2011 23:00:00 +0100</pubDate>
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            <title>Table of Contents</title>
            <link>http://www.medworm.com/index.php?rid=5181097&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D6006638%26arnumber%3D6006648</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <title>Blank page</title>
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            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Thu, 30 Jun 2011 23:00:00 +0100</pubDate>
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            <title>IEEE Transactions on Medical Imaging information for authors</title>
            <link>http://www.medworm.com/index.php?rid=4992274&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D5934478%26arnumber%3D5934481</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Thu, 30 Jun 2011 23:00:00 +0100</pubDate>
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            <title>Have you visited lately? www.ieee.org</title>
            <link>http://www.medworm.com/index.php?rid=4992273&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D5934478%26arnumber%3D5934484</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Thu, 30 Jun 2011 23:00:00 +0100</pubDate>
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            <title>Why we joined</title>
            <link>http://www.medworm.com/index.php?rid=4992272&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D5934478%26arnumber%3D5934483</link>
            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Thu, 30 Jun 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>Accelerating Image Registration With the Johnson&amp;#x2013;Lindenstrauss Lemma: Application to Imaging 3-D Neural Ultrastructure With Electron Microscopy</title>
            <link>http://www.medworm.com/index.php?rid=4992271&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D5934478%26arnumber%3D5728921</link>
            <description>We present a novel algorithm to accelerate feature based registration, and demonstrate the utility of the algorithm for the alignment of large transmission electron microscopy (TEM) images to create 3-D images of neural ultrastructure. In contrast to the most similar algorithms, which achieve small computation times by truncated search, our algorithm uses a novel randomized projection to accelerate feature comparison and to enable global search. Further, we demonstrate robust estimation of nonrigid transformations with a novel probabilistic correspondence framework, that enables large TEM images to be rapidly brought into alignment, removing characteristic distortions of the tissue fixation and imaging process. We analyze the impact of randomized projections upon correspondence detection, ...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Thu, 30 Jun 2011 23:00:00 +0100</pubDate>
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            <title>JIGSAW: Joint Inhomogeneity Estimation via Global Segment Assembly for Water&amp;#x2013;Fat Separation</title>
            <link>http://www.medworm.com/index.php?rid=4992270&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D5934478%26arnumber%3D5723753</link>
            <description>Water&amp;#x2013;fat separation in magnetic resonance imaging (MRI) is of great clinical importance, and the key to uniform water&amp;#x2013;fat separation lies in field map estimation. This work deals with three-point field map estimation, in which water and fat are modelled as two single-peak spectral lines, and field inhomogeneities shift the spectrum by an unknown amount. Due to the simplified spectrum modelling, there exists inherent ambiguity in forming field maps from multiple locally feasible field map values at each pixel. To resolve such ambiguity, spatial smoothness of field maps has been incorporated as a constraint of an optimization problem. However, there are two issues: the optimization problem is computationally intractable and even when it is solved exactly, it does not always se...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4992270</comments>
            <pubDate>Thu, 30 Jun 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>Using Gaussian-Process Regression for Meta-Analytic Neuroimaging Inference Based on Sparse Observations</title>
            <link>http://www.medworm.com/index.php?rid=4992269&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D5934478%26arnumber%3D5723754</link>
            <description>The purpose of neuroimaging meta-analysis is to localize the brain regions that are activated consistently in response to a certain intervention. As a commonly used technique, current coordinate-based meta-analyses (CBMA) of neuroimaging studies utilize relatively sparse information from published studies, typically only using (x,y,z) coordinates of the activation peaks. Such CBMA methods have several limitations. First, there is no way to jointly incorporate deactivation information when available, which has been shown to result in an inaccurate statistic image when assessing a difference contrast. Second, the scale of a kernel reflecting spatial uncertainty must be set without taking the effect size (e.g., Z-stat) into account. To address these problems, we employ Gaussian-process regres...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Thu, 30 Jun 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>Real-Time Image-Based B-Mode Ultrasound Image Simulation of Needles Using Tensor-Product Interpolation</title>
            <link>http://www.medworm.com/index.php?rid=4992268&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D5934478%26arnumber%3D5721837</link>
            <description>In this paper, we propose an interpolation-based method for simulating rigid needles in B-mode ultrasound images in real time. We parameterize the needle B-mode image as a function of needle position and orientation. We collect needle images under various spatial configurations in a water-tank using a needle guidance robot. Then we use multidimensional tensor-product interpolation to simulate images of needles with arbitrary poses and positions using collected images. After further processing, the interpolated needle and seed images are superimposed on top of phantom or tissue image backgrounds. The similarity between the simulated and the real images is measured using a correlation metric. A comparison is also performed with in vivo images obtained during prostate brachytherapy. Our resul...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4992268</comments>
            <pubDate>Thu, 30 Jun 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>Assessment of Averaging Spatially Correlated Noise for 3-D Radial Imaging</title>
            <link>http://www.medworm.com/index.php?rid=4992267&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D5934478%26arnumber%3D5715884</link>
            <description>Any measurement of signal intensity obtained from an image will be corrupted by noise. If the measurement is from one voxel, an error bound associated with noise can be assigned if the standard deviation of noise in the image is known. If voxels are averaged together within a region of interest (ROI) and the image noise is uncorrelated, the error bound associated with noise will be reduced in proportion to the square root of the number of voxels in the ROI. However, when 3-D-radial images are created the image noise will be spatially correlated. In this paper, an equation is derived and verified with simulated noise for the computation of noise averaging when image noise is correlated, facilitating the assessment of noise characteristics for different 3-D-radial imaging methodologies. It i...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Thu, 30 Jun 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>A Model Selection Method for Nonlinear System Identification Based fMRI Effective Connectivity Analysis</title>
            <link>http://www.medworm.com/index.php?rid=4992266&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D5934478%26arnumber%3D5714750</link>
            <description>In this paper a model selection algorithm for a nonlinear system identification method is proposed to study functional magnetic resonance imaging (fMRI) effective connectivity. Unlike most other methods, this method does not need a pre-defined structure/model for effective connectivity analysis. Instead, it relies on selecting significant nonlinear or linear covariates for the differential equations to describe the mapping relationship between brain output (fMRI response) and input (experiment design). These covariates, as well as their coefficients, are estimated based on a least angle regression (LARS) method. In the implementation of the LARS method, Akaike's information criterion corrected (AICc) algorithm and the leave-one-out (LOO) cross-validation method were employed and compared f...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4992266</comments>
            <pubDate>Thu, 30 Jun 2011 23:00:00 +0100</pubDate>
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        <item>
            <title>Weighted Maximum Posterior Marginals for Random Fields Using an Ensemble of Conditional Densities From Multiple Markov Chain Monte Carlo Simulations</title>
            <link>http://www.medworm.com/index.php?rid=4992265&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D5934478%26arnumber%3D5713842</link>
            <description>The ability of classification systems to adjust their performance (sensitivity/specificity) is essential for tasks in which certain errors are more significant than others. For example, mislabeling cancerous lesions as benign is typically more detrimental than mislabeling benign lesions as cancerous. Unfortunately, methods for modifying the performance of Markov random field (MRF) based classifiers are noticeably absent from the literature, and thus most such systems restrict their performance to a single, static operating point (a paired sensitivity/specificity). To address this deficiency we present weighted maximum posterior marginals (WMPM) estimation, an extension of maximum posterior marginals (MPM) estimation. Whereas the MPM cost function penalizes each error equally, the WMPM cost...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
        <comments>http://www.medworm.com/rss/comments.php?id=4992265</comments>
            <pubDate>Thu, 30 Jun 2011 23:00:00 +0100</pubDate>
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            <title>A Maximum NEC Criterion for Compton Collimation to Accurately Identify True Coincidences in PET</title>
            <link>http://www.medworm.com/index.php?rid=4992264&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D5934478%26arnumber%3D5711670</link>
            <description>We present an algorithm for choosing the incident photon direction window threshold that maximizes the noise equivalent counts of the PET system. For simulated data, the direction window removed 56%&amp;#x2013;67% of random coincidences while retaining ${&gt; 94}%$ of true coincidences from image reconstruction as well as accurately extracted 70% of true coincidences from multiple coincidences. (Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Thu, 30 Jun 2011 23:00:00 +0100</pubDate>
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            <title>Total Variation Regularization for fMRI-Based Prediction of Behavior</title>
            <link>http://www.medworm.com/index.php?rid=4992263&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D5934478%26arnumber%3D5711672</link>
            <description>While medical imaging typically provides massive amounts of data, the extraction of relevant information for predictive diagnosis remains a difficult challenge. Functional magnetic resonance imaging (fMRI) data, that provide an indirect measure of task-related or spontaneous neuronal activity, are classically analyzed in a mass-univariate procedure yielding statistical parametric maps. This analysis framework disregards some important principles of brain organization: population coding, distributed and overlapping representations. Multivariate pattern analysis, i.e., the prediction of behavioral variables from brain activation patterns better captures this structure. To cope with the high dimensionality of the data, the learning method has to be regularized. However, the spatial structure ...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Thu, 30 Jun 2011 23:00:00 +0100</pubDate>
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            <title>Perception-Based Visualization of Manifold-Valued Medical Images Using Distance-Preserving Dimensionality Reduction</title>
            <link>http://www.medworm.com/index.php?rid=4992262&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D5934478%26arnumber%3D5709986</link>
            <description>A method for visualizing manifold-valued medical image data is proposed. The method operates on images in which each pixel is assumed to be sampled from an underlying manifold. For example, each pixel may contain a high dimensional vector, such as the time activity curve (TAC) in a dynamic positron emission tomography (dPET) or a dynamic single photon emission computed tomography (dSPECT) image, or the positive semi-definite tensor in a diffusion tensor magnetic resonance image (DTMRI). A nonlinear mapping reduces the dimensionality of the pixel data to achieve two goals: distance preservation and embedding into a perceptual color space. We use multidimensional scaling distance-preserving mapping to render similar pixels (e.g., DT or TAC pixels) with perceptually similar colors. The 3D CIE...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Thu, 30 Jun 2011 23:00:00 +0100</pubDate>
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            <title>Voxel-Based Adaptive Spatio-Temporal Modelling of Perfusion Cardiovascular MRI</title>
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            <description>Contrast enhanced myocardial perfusion magnetic resonance imaging (MRI) is a promising technique, providing insight into how reduced coronary flow affects the myocardial tissue. Stenosis in a coronary vessel leads to reduced myocardial blood flow, but collaterals may secure the blood supply of the myocardium, with altered tracer kinetics. Due to a low signal-to-noise ratio, quantitative analysis of the signal is typically difficult to achieve at the voxel level. Hence, analysis is often performed on measurements that are aggregated in predefined myocardial segments, that ignore the variability in blood flow in each segment. The approach presented in this paper uses local spatial information that enables one to perform a robust analysis at the voxel level. The spatial dependencies between l...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Thu, 30 Jun 2011 23:00:00 +0100</pubDate>
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            <description>(Source: IEE Transactions on Medical Imaging)</description>
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            <title>Table of Contents</title>
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            <description>(Source: IEE Transactions on Medical Imaging)</description>
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            <title>Blank page</title>
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            <description>(Source: IEE Transactions on Medical Imaging)</description>
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            <pubDate>Tue, 31 May 2011 23:00:00 +0100</pubDate>
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            <title>IEEE Transactions on Medical Imaging information for authors</title>
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            <description>(Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <pubDate>Tue, 31 May 2011 23:00:00 +0100</pubDate>
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            <title>Explore IEL IEEE's most comprehensive resource</title>
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            <description>(Source: IEE Transactions on Medical Imaging)</description>
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            <pubDate>Tue, 31 May 2011 23:00:00 +0100</pubDate>
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            <title>Mobi health</title>
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            <description>(Source: IEE Transactions on Medical Imaging)</description>
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            <pubDate>Tue, 31 May 2011 23:00:00 +0100</pubDate>
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            <title>Testing for Spatial Heterogeneity in Functional MRI Using the Multivariate General Linear Model</title>
            <link>http://www.medworm.com/index.php?rid=4911207&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D5779922%26arnumber%3D5713258</link>
            <description>Much current research in functional magnetic resonance imaging (fMRI) employs multivariate machine learning approaches (e.g., support vector machines) to detect distributed spatial patterns from the temporal fluctuations of the neural signal. The aim of many studies is not classification, however, but investigation of multivariate spatial patterns, which pattern classifiers detect only indirectly. Here we propose a direct statistical measure for the existence of distributed spatial patterns (or spatial heterogeneity) applicable to fMRI datasets. We extend the univariate general linear model (GLM), typically used in fMRI analysis, to a multivariate case. We demonstrate that contrasting maximum likelihood estimations of different restrictions on this multivariate model can be used to estimat...</description>
            <author>IEE Transactions on Medical Imaging</author>
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            <title>Prediction of the Spatial Resolution of Magnetic Particle Imaging Using the Modulation Transfer Function of the Imaging Process</title>
            <link>http://www.medworm.com/index.php?rid=4911206&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D5779922%26arnumber%3D5711671</link>
            <description>The magnetic particle imaging method allows for the quantitative determination of spatial distributions of superparamagnetic nanoparticles in vivo. Recently, it was shown that the 1-D magnetic particle imaging process can be formulated as a convolution. Analyzing the width of the convolution kernel allows for predicting the spatial resolution of the method. However, this measure does not take into account the noise of the measured data. Furthermore, it does not consider a reconstruction step, which can increase the resolution beyond the width of the convolution kernel. In this paper, the spatial resolution of magnetic particle imaging is investigated by analyzing the modulation transfer function of the imaging process. An expression for the spatial resolution is derived, which includes the...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Tue, 31 May 2011 23:00:00 +0100</pubDate>
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            <title>Fiber Continuity: An Anisotropic Prior for ODF Estimation</title>
            <link>http://www.medworm.com/index.php?rid=4911205&amp;cid=s_37226_169_f&amp;fid=37226&amp;url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Fisnumber%3D5779922%26arnumber%3D5710983</link>
            <description>The accurate and reliable estimation of fiber orientation distributions, based on diffusion-sensitized magnetic resonance images is a major prerequisite for tractography algorithms or any other derived statistical analysis. In this work, we formulate the principle of fiber continuity (FC), which is based on the simple observation that the imaging of fibrous tissue implies certain expectations for the measured images. From this principle we derive a prior for the estimation of fiber orientation distributions based on high angular resolution diffusion imaging (HARDI). We demonstrate on simulated, phantom, and in vivo data the superiority of the proposed approach. Further, we propose another application of the FC principle, named FC flow, a method to resolve complex crossing regions solely ba...</description>
            <author>IEE Transactions on Medical Imaging</author>
            <type>journals</type>
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            <pubDate>Tue, 31 May 2011 23:00:00 +0100</pubDate>
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            <title>Hybrid Small Animal Imaging System Combining Magnetic Resonance Imaging With Fluorescence Tomography Using Single Photon Avalanche Diode Detectors</title>
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            <description>We describe an integrated system for small animal imaging incorporating a noncontact fluorescence molecular tomography (FMT) system into an MRI detector. By adopting a free laser beam design geometrical constraints imposed by the use of optical fibers could be avoided allowing for flexible fluorescence excitation schemes. Photon detection based on a single-photon avalanche diode array enabled simultaneous FMT/MRI measurements without interference between modalities. In vitro characterization revealed good spatial accuracy of FMT data and accurate quantification of dye concentrations. Feasibility of FMT/MRI was demonstrated in vivo by simultaneous assessment of protease activity and tumor morphology in murine colon cancer xenografts. (Source: IEE Transactions on Medical Imaging)</description>
            <author>IEE Transactions on Medical Imaging</author>
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