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On the Epsilon Most Stringent Test Between Two Vector Lines in Gaussian Noise
This paper addresses the problem of distinguishing between two vector lines observed through noisy measurements. This is a hypothesis testing problem where the two hypotheses are composite since the signal amplitudes are deterministic and not known. An ideal criterion of optimality, namely the most stringent test, consists in minimizing the maximum shortcoming of the test subject to a constrained false alarm probability. The maximum shortcoming corresponds to the maximum gap between the power function of the test and the envelope power function which is defined as the supremum of the power over all tests satisfying the pre...
Source: IEEE Transactions on Signal Processing - September 2, 2014 Category: Biomedical Engineering Source Type: research

A Steered-Response Power Algorithm Employing Hierarchical Search for Acoustic Source Localization Using Microphone Arrays
The localization of a speaker inside a closed environment is often approached by real-time processing of multiple audio signals captured by a set of microphones. One of the leading related methods for sound source localization, the steered-response power (SRP), searches for the point of maximum power over a spatial grid. High-accuracy localization calls for a dense grid and/or many microphones, which tends to impractically increase computational requirements. This paper proposes a new method for sound source localization (called H-SRP), which applies the SRP approach to space regions instead of grid points. This arrangemen...
Source: IEEE Transactions on Signal Processing - September 2, 2014 Category: Biomedical Engineering Source Type: research

Enabling D2D Communications Through Neighbor Discovery in LTE Cellular Networks
This work studies the problem of neighbor discovery for device-to-device (D2D) communications of LTE user equipments (UEs) in a modern cellular network. By listening to cellular uplink transmissions, UEs can detect potential D2D partners through a neighbor discovery process compatible with the standard LTE network protocol. We focus on neighbor discovery utilizing sounding reference signal (SRS) channel, which can be accessed by peer UEs that are LTE-compliant. Under the constraint of unknown channel statistics during uplink hearing, we propose joint neighbor detection and D2D channel estimation for listening UEs using the...
Source: IEEE Transactions on Signal Processing - September 2, 2014 Category: Biomedical Engineering Source Type: research

Regularized Tyler's Scatter Estimator: Existence, Uniqueness, and Algorithms
This paper considers the regularized Tyler's scatter estimator for elliptical distributions, which has received considerable attention recently. Various types of shrinkage Tyler's estimators have been proposed in the literature and proved work effectively in the “large $p$ small $n$” scenario. Nevertheless, the existence and uniqueness properties of the estimators are not thoroughly studied, and in certain cases the algorithms may fail to converge. In this work, we provide a general result that analyzes the sufficient condition for the existence of a family of shrinkage Tyler's estimators, which quantitativel...
Source: IEEE Transactions on Signal Processing - September 2, 2014 Category: Biomedical Engineering Source Type: research

Table of contents
Presents the table of contents for this issue of the periodical. (Source: IEEE Transactions on Signal Processing)
Source: IEEE Transactions on Signal Processing - September 2, 2014 Category: Biomedical Engineering Source Type: research

Impact of the control for corrupted diffusion tensor imaging data in comparisons at the group level: an application in Huntington disease
Conclusion: An impact on the result patterns of the comparison of FA maps between HD subjects and controls was observed depending on whether QC-based elimination of corrupted GD was performed. QC-based elimination of corrupted GD in DTI scans reduces the risk of type I and type II errors in cross-sectional group comparison of FA maps contributing to an increase in reliability and stability of group comparisons. (Source: BioMedical Engineering OnLine)
Source: BioMedical Engineering OnLine - September 1, 2014 Category: Biomedical Engineering Authors: Hans-Peter MüllerJan KassubekGeorg GrönReiner SprengelmeyerAlbert LudolphStefan KlöppelNicola HobbsRaymund RoosAlexandra DuerrSarah TabriziMichael OrthSigurd SüssmuthGeorg Landwehrmeyer Source Type: research

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Source: IEE Transactions on Medical Imaging - September 1, 2014 Category: Biomedical Engineering Source Type: research

Parameterization and reliability of single-leg balance test assessed with inertial sensors in stroke survivors: a cross-sectional study
Conclusion: There were no significant differences between the kinematic records made by an inertial sensor during the development of the SLS testing between two inertial sensors placed in the lumbar and thoracic regions. In addition, inertial sensors. Have the potential to be reliable, valid and sensitive instruments for kinematic measurements during SLS testing but further research is needed. (Source: BioMedical Engineering OnLine)
Source: BioMedical Engineering OnLine - August 30, 2014 Category: Biomedical Engineering Authors: David Perez-CruzadoManuel González-SánchezAntonio Cuesta-Vargas Source Type: research

Joint Interference Mitigation and Data Recovery in Compressive Domain: A Sparse MLE Approach
We consider the problem where a receiver acquires information (data) corrupted by interference and noise. Both the information and interference are assumed to have a sparse structure. This problem occurs in many applications such as data demodulation in cellular systems. The joint interference mitigation and data recovery is formulated as a sparse maximum likelihood estimation (MLE) problem which maximizes the associated likelihood function under individual sparsity levels (ISLs) constraints. This sparse MLE framework can fully exploit the individual sparse structure of the information and interference to improve the data ...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

Convergence Analysis of the Variance in Gaussian Belief Propagation
It is known that Gaussian belief propagation (BP) is a low-complexity algorithm for (approximately) computing the marginal distribution of a high dimensional Gaussian distribution. However, in loopy factor graph, it is important to determine whether Gaussian BP converges. In general, the convergence conditions for Gaussian BP variances and means are not necessarily the same, and this paper focuses on the convergence condition of Gaussian BP variances. In particular, by describing the message-passing process of Gaussian BP as a set of updating functions, the necessary and sufficient convergence conditions of Gaussian BP var...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

Weighted Fair Multicast Multigroup Beamforming Under Per-antenna Power Constraints
A multiantenna transmitter that conveys independent sets of common data to distinct groups of users is considered. This model is known as physical layer multicasting to multiple cochannel groups. In this context, the practical constraint of a maximum permitted power level radiated by each antenna is addressed. The per-antenna power constrained system is optimized in a maximum fairness sense with respect to predetermined quality of service weights. In other words, the worst scaled user is boosted by maximizing its weighted signal-to-interference plus noise ratio. A detailed solution to tackle the weighted max-min fair multi...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

Performance Metrics, Sampling Schemes, and Detection Algorithms for Wideband Spectrum Sensing
In this paper, we study the problem of wideband spectrum sensing for cognitive radio networks by partitioning it into four fundamental elements: system modeling, performance metrics, sampling schemes, and detection algorithms. Each element can potentially couple the individual channels so that designs for wideband spectrum sensing should consider the four elements jointly. We propose the $p$-sparse model for the primary occupancies and study three uniform sampling schemes for wideband spectrum sensing, specifically, partial-band Nyquist sampling, sequential narrowband Nyquist sampling, and integer undersampling. We suggest...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

Variable-Rate Transmission for MIMO Time-Correlated Channels With Limited Feedback
In this paper we consider variable-rate transmission for time-correlated MIMO (multi-input multi-output) channels with limited feedback. The number of bits loaded on each subchannel of the MIMO system is dynamically assigned according to the current channel condition and fed back to the transmitter. As the channel is time-correlated, bit loading is a vector signal that is also time-correlated. We propose to feedback bit loading using predictive coding, which is known to be a powerful quantization technique when the underlying signal is correlated in time. Assuming the channel is a first-order Gauss-Markov random process, w...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

Divergence-Based Soft Decision for Error Resilient Decentralized Signal Detection
In this paper, we consider decentralized detection where the transmission of local soft-decisions of the secondary users (SUs) to the fusion center (FC) is both rate-limited and error-prone. The quantized data to be sent from SUs should not only carry the local information but also need to be resilient to channel errors. With the assumption of independent and identical secondary user observations conditioned on signal hypothesis and binary symmetric channels (BSC) between SUs and the FC, we design local quantizers at a SU, based on two divergence metrics, namely Kullback–Leibler (KL) and Chernoff. Using convex duali...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

The Restricted Isometry Property for Banded Random Matrices
In this paper, we investigate the problem of determining the conditions under which the restricted isometry property (RIP) is satisfied for a particular type of matrix referred to in here as a banded random matrix (BRM). Such matrices have been recognized as suitable models for a number of compressive-sensing based sampling architectures, including the interleaved random demodulator, the random demodulator, the parallel non-interleaved random demodulator, the random sampler, and the periodic nonuniform sampler. It is thus important to establish the conditions under which the BRM satisfies the RIP; to our knowledge, this qu...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

OMP Based Joint Sparsity Pattern Recovery Under Communication Constraints
We address the problem of joint sparsity pattern recovery based on multiple measurement vectors (MMVs) in resource constrained distributed networks. We assume that distributed nodes observe sparse signals that share a common (but unknown) sparsity pattern. Each node is assumed to sample the sparse signals via different sensing matrices in general. In many distributed communication networks, it is often required that joint sparse recovery be performed under inherent resource constraints such as communication bandwidth and transmit/processing power. We propose two approaches to take the communication constraints into account...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

Optimal Spectrum Leasing and Resource Sharing in Two-Way Relay Networks
Assuming a bidirectional relay assisted network, we study the problem of optimal resource sharing between two transceiver pairs. One pair, referred to as the primary pair, is considered to be the owner of the spectral resources. The rates of the two transceivers in this pair must be guaranteed to be greater than a predefined threshold. The second pair, called the secondary pair, is assumed to own the relay infrastructure. The secondary network allows the primary pair to use the relays to establish a bidirectional communication between its transceivers. In exchange for this cooperation, the primary pair assigns a portion of...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

Optimal Algorithms for $L_{1}$-subspace Signal Processing
We describe ways to define and calculate $L_{1}$-norm signal subspaces that are less sensitive to outlying data than $L_{2}$ -calculated subspaces. We start with the computation of the $L_{1}$ maximum-projection principal component of a data matrix containing $N$ signal samples of dimension $D$. We show that while the general problem is formally NP-hard in asymptotically large $N$, $D$, the case of engineering interest of fixed dimension $D$ and asymptotically large sample size $N$ is not. In particular, for the case where the sample size is less than the fixed dimension $(N < D)$, we present in explicit form an optimal...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

Super-Resolution Reconstruction in Frequency-Domain Optical-Coherence Tomography Using the Finite-Rate-of-Innovation Principle
We present results of Monte Carlo analyses, and assess statistical efficiency of the reconstruction techniques by comparing their performance against the Cramér-Rao bound. Reconstruction results on experimental data obtained from technical as well as biological specimens show a distinct improvement in resolution and signal-to-reconstruction noise offered by the proposed method in comparison with the standard approach. (Source: IEEE Transactions on Signal Processing)
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

Compressive Sparsity Order Estimation for Wideband Cognitive Radio Receiver
Compressive sensing (CS) has been widely investigated in the cognitive radio (CR) literature in order to reduce the hardware cost of sensing wideband signals assuming prior knowledge of the sparsity pattern. However, the sparsity order of the channel occupancy is time-varying and the sampling rate of the CS receiver needs to be adjusted based on its value in order to fully exploit the potential of CS-based techniques. In this context, investigating blind sparsity order estimation (SOE) techniques is an open research issue. To address this, we study an eigenvalue-based compressive SOE technique using asymptotic random matri...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

Joint Sparse Recovery Method for Compressed Sensing With Structured Dictionary Mismatches
In traditional compressed sensing theory, the dictionary matrix is given a priori, whereas in real applications this matrix suffers from random noise and fluctuations. In this paper, we consider a signal model where each column in the dictionary matrix is affected by a structured noise. This formulation is common in direction-of-arrival (DOA) estimation of off-grid targets, encountered in both radar systems and array processing. We propose to use joint sparse signal recovery to solve the compressed sensing problem with structured dictionary mismatches and also give an analytical performance bound on this joint sparse recov...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

Time-Switching Uplink Network-Coded Cooperative Communication With Downlink Energy Transfer
In this work, we consider a multiuser cooperative wireless network where the energy-constrained sources have independent information to transmit to a common destination, which is assumed to be externally powered and responsible for transferring energy wirelessly to the sources. The source nodes may cooperate, under either decode-and-forward or network coding-based protocols. Taking into account the fact that the energy harvested by the source nodes is a function of the fading realization of inter-user channels and user-destination channels, we obtain a closed-form approximation for the system outage probability, as well as...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

A Discretization-Free Sparse and Parametric Approach for Linear Array Signal Processing
Direction of arrival (DOA) estimation in array processing using uniform/sparse linear arrays is concerned in this paper. While sparse methods via approximate parameter discretization have been popular in the past decade, the discretization may cause problems, e.g., modeling error and increased computations due to dense sampling. In this paper, an exact discretization-free method, named as sparse and parametric approach (SPA), is proposed for uniform and sparse linear arrays. SPA carries out parameter estimation in the continuous range based on well-established covariance fitting criteria and convex optimization. It guarant...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

A Coordinate Descent Algorithm for Complex Joint Diagonalization Under Hermitian and Transpose Congruences
This paper deals with the problem of joint complex matrix diagonalization by considering both the Hermitian and transpose congruences. We address the general case where the searched diagonalizing matrix is a priori nonunitary. Based on the minimization of a quadratic criterion, we propose a flexible algorithm in the sense that it allows to directly consider a rectangular diagonalizing matrix and to take into consideration both the Hermitian and transpose congruences within the same framework. The proposed algorithm is a coordinate descent algorithm that is based on an approximate criterion leading to the analytical derivat...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

Distributed Compressed Sensing for Static and Time-Varying Networks
We consider the problem of in-network compressed sensing from distributed measurements. Every agent has a set of measurements of a signal $x$ , and the objective is for the agents to recover $x$ from their collective measurements using only communication with neighbors in the network. Our distributed approach to this problem is based on the centralized Iterative Hard Thresholding algorithm (IHT). We first present a distributed IHT algorithm for static networks that leverages standard tools from distributed computing to execute in-network computations with minimized bandwidth consumption. Next, we address distributed signal...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

A Linear Source Recovery Method for Underdetermined Mixtures of Uncorrelated AR-Model Signals Without Sparseness
Conventional sparseness-based approaches for instantaneous underdetermined blind source separation (UBSS) do not take into account the temporal structure of the source signals. In this work, we exploit the source temporal structure and propose a linear source recovery solution for the UBSS problem which does not require the source signals to be sparse. Assuming the source signals are uncorrelated and can be modeled by an autoregressive (AR) model, the proposed algorithm is able to estimate the source AR coefficients from the mixtures given the mixing matrix. We prove that the UBSS problem can be converted into a determined...
Source: IEEE Transactions on Signal Processing - August 29, 2014 Category: Biomedical Engineering Source Type: research

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(Source: IEE Transactions on Medical Imaging)
Source: IEE Transactions on Medical Imaging - August 29, 2014 Category: Biomedical Engineering Source Type: research

Two-Dimensional Compressed Sensing Using the Cross-sampling Approach for Low-Field MRI Systems
A compressed sensing method using a cross sampling and self-calibrated off-resonance correction is proposed. Estimation of the magnetic field inhomogeneity based on image registration enables the off-resonance correction with no additional radio-frequency pulses or acquisitions. In addition to this advantage, a fast and straightforward calculation was achieved by using the first-order components of the magnetic field inhomogeneity. Imaging experiments using a phantom and a chemically fixed mouse demonstrated practical benefits in improving blurring and artifacts in magnetic resonance images in low field magnetic resonance ...
Source: IEE Transactions on Medical Imaging - August 29, 2014 Category: Biomedical Engineering Source Type: research

IEEE Transactions on Medical Imaging information for authors
(Source: IEE Transactions on Medical Imaging)
Source: IEE Transactions on Medical Imaging - August 29, 2014 Category: Biomedical Engineering Source Type: research

The Isometric Log-Ratio Transform for Probabilistic Multi-Label Anatomical Shape Representation
Sources of uncertainty in the boundaries of structures in medical images have motivated the use of probabilistic labels in segmentation applications. An important component in many medical image segmentation tasks is the use of a shape model, often generated by applying statistical techniques to training data. Standard statistical techniques (e.g., principal component analysis) often assume data lies in an unconstrained vector space, but probabilistic labels are constrained to the unit simplex. If these statistical techniques are used directly on probabilistic labels, relative uncertainty information can be sacrificed. A s...
Source: IEE Transactions on Medical Imaging - August 29, 2014 Category: Biomedical Engineering Source Type: research

Optoacoustic Imaging of Subcutaneous Microvasculature With a Class one Laser
We developed a combined imaging platform allowing optoacoustic and ultrasound imaging based on a low energy laser and a handheld probe. The device is based on a sensitive single element 35-MHz focused transducer, a 2-D piezoscanner and a dual-wavelength switchable Nd:YAG laser. Acoustical detection and optical illumination are confocal for optimization of optoacoustic signal-to-noise ratio. The system allows to scan over a range up to 12 mm $times $12 mm in xy-direction with an isotropic lateral resolution of about 90 ${mu{hbox {m}}}$. Although the device is a class 1 laser product having pulse energies in the $< 100~{m...
Source: IEE Transactions on Medical Imaging - August 29, 2014 Category: Biomedical Engineering Source Type: research

Local Optimization Based Segmentation of Spatially-Recurring, Multi-Region Objects With Part Configuration Constraints
Abstract—Incorporating prior knowledge into image segmentation algorithms has proven useful for obtaining more accurate and plausible results. Two important constraints, containment and exclusion of regions, have gained attention in recent years mainly due to their descriptive power. In this paper, we augment the level set framework with the ability to handle these two intuitive geometric relationships, containment and exclusion, along with a distance constraint between boundaries of multi-region objects. Level set’s important property of automatically handling topological changes of evolving contours/surface...
Source: IEE Transactions on Medical Imaging - August 29, 2014 Category: Biomedical Engineering Source Type: research

Noninvasive Transmural Electrophysiological Imaging Based on Minimization of Total-Variation Functional
We present a variational TV-prior instead of a common discrete TV-prior for improved robustness to mesh resolution, and solve the TV-minimization by a sequence of weighted, first-order L2-norm minimization. In a large set of phantom experiments, the proposed method is shown to outperform existing quadratic methods in preserving the steep gradient of action potential along the border of infarcts, as well as in capturing the disruption to the normal path of electrical wavefronts. Real-data experiments also further demonstrate the potential of the proposed method in revealing the location and shape of infarcts when quadratic ...
Source: IEE Transactions on Medical Imaging - August 29, 2014 Category: Biomedical Engineering Source Type: research

Tracking Using Motion Estimation With Physically Motivated Inter-Region Constraints
We propose a method for tracking structures (e.g., ventricles and myocardium) in cardiac images (e.g., magnetic resonance) by propagating forward in time a previous estimate of the structures using a new physically motivated motion estimation scheme. Our method estimates motion by regularizing only within structures so that differing motions among different structures are not mixed. It simultaneously satisfies the physical constraints at the interface between a fluid and a medium that the normal component of the fluid's motion must match the normal component of the medium's motion and the No-Slip condition, which states th...
Source: IEE Transactions on Medical Imaging - August 29, 2014 Category: Biomedical Engineering Source Type: research

Model-Based MR Parameter Mapping With Sparsity Constraints: Parameter Estimation and Performance Bounds
Magnetic resonance parameter mapping (e.g., $T_{1}$ mapping, $T_{2}$ mapping, $T^{ast }_{2}$ mapping) is a valuable tool for tissue characterization. However, its practical utility has been limited due to long data acquisition time. This paper addresses this problem with a new model-based parameter mapping method. The proposed method utilizes a formulation that integrates the explicit signal model with sparsity constraints on the model parameters, enabling direct estimation of the parameters of interest from highly undersampled, noisy $ {bf k}$-space data. An efficient greedy-pursuit algorithm is described to solve the res...
Source: IEE Transactions on Medical Imaging - August 29, 2014 Category: Biomedical Engineering Source Type: research

A Fourier-Based Approach to the Angiographic Assessment of Flow Diverter Efficacy in the Treatment of Cerebral Aneurysms
Flow diversion is an emerging endovascular treatment option for cerebral aneurysms. Quantitative assessment of hemodynamic changes induced by flow diversion can aid clinical decision making in the treatment of cerebral aneurysms. In this article, besides summarizing past key research efforts, we propose a novel metric for the angiographic assessment of flow diverter deployments in the treatment of cerebral aneurysms. By analyzing the frequency spectra of signals derived from digital subtraction angiography (DSA) series, the metric aims to quantify the prevalence of frequency components that correspond to the patient-specif...
Source: IEE Transactions on Medical Imaging - August 29, 2014 Category: Biomedical Engineering Source Type: research

Multiatlas Segmentation as Nonparametric Regression
We describe how to estimate these parameters and show that several human anatomical structures exhibit the trends modeled analytically. We use these parameter estimates to optimize the regression estimator. We show that the expected error for large database sizes is well predicted by models learned on small databases. Thus, a few expert segmentations can help predict the database sizes required to keep the expected error below a specified tolerance level. Such cost-benefit analysis is crucial for deploying clinical multiatlas segmentation systems. (Source: IEE Transactions on Medical Imaging)
Source: IEE Transactions on Medical Imaging - August 29, 2014 Category: Biomedical Engineering Source Type: research

Automatic Whole Brain MRI Segmentation of the Developing Neonatal Brain
In this study, we propose a framework for accurate intensity-based segmentation of the developing neonatal brain, from the early preterm period to term-equivalent age, into 50 brain regions. We present a novel segmentation algorithm that models the intensities across the whole brain by introducing a structural hierarchy and anatomical constraints. The proposed method is compared to standard atlas-based techniques and improves label overlaps with respect to manual reference segmentations. We demonstrate that the proposed technique achieves highly accurate results and is very robust across a wide range of gestational ages, f...
Source: IEE Transactions on Medical Imaging - August 29, 2014 Category: Biomedical Engineering Source Type: research

Hierarchical Lung Field Segmentation With Joint Shape and Appearance Sparse Learning
Lung field segmentation in the posterior–anterior (PA) chest radiograph is important for pulmonary disease diagnosis and hemodialysis treatment. Due to high shape variation and boundary ambiguity, accurate lung field segmentation from chest radiograph is still a challenging task. To tackle these challenges, we propose a joint shape and appearance sparse learning method for robust and accurate lung field segmentation. The main contributions of this paper are: 1) a robust shape initialization method is designed to achieve an initial shape that is close to the lung boundary under segmentation; 2) a set of local sparse ...
Source: IEE Transactions on Medical Imaging - August 29, 2014 Category: Biomedical Engineering Source Type: research

7T Transmit/Receive Arrays Using ICE Decoupling for Human Head MR Imaging
In this study, an eight-channel transmit/receive volume array with ICE-decoupled loop elements was built and investigated to demonstrate its feasibility and robustness for human head imaging at 7T. Isolation between adjacent loop elements was better than - 25 dB with a human head load. The worst-case of the isolation between all of the elements was about - 17.5 dB. All of the MRI experiments were performed on a 7T whole-body human MR scanner. Images of the phantom and human head were acquired and ${rm g}$-factor maps were measured and calculated to evaluate the performance of the coil array. Compared with the conventional ...
Source: IEE Transactions on Medical Imaging - August 29, 2014 Category: Biomedical Engineering Source Type: research

Table of Contents
(Source: IEE Transactions on Medical Imaging)
Source: IEE Transactions on Medical Imaging - August 29, 2014 Category: Biomedical Engineering Source Type: research

IEEE Transactions on Medical Imaging publication information
(Source: IEE Transactions on Medical Imaging)
Source: IEE Transactions on Medical Imaging - August 29, 2014 Category: Biomedical Engineering Source Type: research

Bio-insecticide Bacillus thuringiensis spores encapsulated with amaranth derivatized starches: studies on the propagation "in vitro"
The objective of this study was to develop and characterize native and modified amaranth starch granules and evaluate their potential application as wall materials in the microcapsulation of B thuringiensis serovar kurstaki HD-1 (Bt- HD1), produced by spray drying. Native amaranth starch granules were treated by hydrolyzation, high energy milling (HEM) and were chemically modified by phosphorylation and succinylation. The size of the Bt microcapsules varied from 12.99 to 17.14 μm adequate to protect the spores of Bt from ultraviolet radiation. The aw coefficient of the microcapsules produced by the modified starches afte...
Source: Bioprocess and Biosystems Engineering - August 29, 2014 Category: Biomedical Engineering Authors: Rodríguez AP, Martínez MG, Barrera-Cortés J, Ibarra JE, Bustos FM Tags: Bioprocess Biosyst Eng Source Type: research

Lamina replacement with titanium plate fixation improves spinal stability after total lumbar laminectomy.
Abstract Biomechanical experiments and strain analyses were performed to investigate the effects of lamina replacement surgery for intraspinal lesions on postoperative spinal stability. Eight specimens of thoracic and lumbar vertebrae (T12-L4) were collected from adult cadavers. Stepwise lumbar total laminectomy, and laminoplasty with lamina reduction and replacement was undertaken in combination with titanium-plate fixation to simulate the surgical setting. The effects of thoracic and lumbar vertebral strain, displacement, and rigidity on spinal stability were measured following both single and multiple segment la...
Source: Computer Methods in Biomechanics and Biomedical Engineering - August 29, 2014 Category: Biomedical Engineering Authors: Nong L, Zhou D, Xu N, Du R, Jiang X Tags: Comput Methods Biomech Biomed Engin Source Type: research

Identification and monitoring of brain activity based on stochastic relevance analysis of short--time EEG rhythms
Conclusions: The proposed approach provides the reliable identification of traces of interictal/ictal states of epilepsy. The introduced relevance rhythm diagrams of physiological rhythms provides effective means of monitoring epileptic seizures; additionally, these diagrams are easily implement and provide simple clinical interpretation. The developed variability-based relevance analysis can betranslated to other monitoring applications involving time-variant biomedical data. (Source: BioMedical Engineering OnLine)
Source: BioMedical Engineering OnLine - August 28, 2014 Category: Biomedical Engineering Authors: Leonardo Duque MunozCesar Castellanos DomínguezJairo Espinosa Oviedo Source Type: research