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Sian: style-guided instance-adaptive normalization for multi-organ histopathology image synthesis
Proc IEEE Int Symp Biomed Imaging. 2023 Apr;2023:10.1109/isbi53787.2023.10230507. doi: 10.1109/isbi53787.2023.10230507. Epub 2023 Sep 1.ABSTRACTExisting deep neural networks for histopathology image synthesis cannot generate image styles that align with different organs, and cannot produce accurate boundaries of clustered nuclei. To address these issues, we propose a style-guided instance-adaptive normalization (SIAN) approach to synthesize realistic color distributions and textures for histopathology images from different organs. SIAN contains four phases, semantization, stylization, instantiation, and modulation. The fir...
Source: Proceedings - International Symposium on Biomedical Imaging - April 4, 2024 Category: Radiology Authors: Haotian Wang Min Xian Aleksandar Vakanski Bryar Shareef Source Type: research

Enhanced sharp-gan for histopathology image synthesis
Proc IEEE Int Symp Biomed Imaging. 2023 Apr;2023:10.1109/isbi53787.2023.10230516. doi: 10.1109/isbi53787.2023.10230516. Epub 2023 Sep 1.ABSTRACTHistopathology image synthesis aims to address the data shortage issue in training deep learning approaches for accurate cancer detection. However, existing methods struggle to produce realistic images that have accurate nuclei boundaries and less artifacts, which limits the application in downstream tasks. To address the challenges, we propose a novel approach that enhances the quality of synthetic images by using nuclei topology and contour regularization. The proposed approach u...
Source: Proceedings - International Symposium on Biomedical Imaging - April 4, 2024 Category: Radiology Authors: Sujata Butte Haotian Wang Aleksandar Vakanski Min Xian Source Type: research

Sian: style-guided instance-adaptive normalization for multi-organ histopathology image synthesis
Proc IEEE Int Symp Biomed Imaging. 2023 Apr;2023:10.1109/isbi53787.2023.10230507. doi: 10.1109/isbi53787.2023.10230507. Epub 2023 Sep 1.ABSTRACTExisting deep neural networks for histopathology image synthesis cannot generate image styles that align with different organs, and cannot produce accurate boundaries of clustered nuclei. To address these issues, we propose a style-guided instance-adaptive normalization (SIAN) approach to synthesize realistic color distributions and textures for histopathology images from different organs. SIAN contains four phases, semantization, stylization, instantiation, and modulation. The fir...
Source: Proceedings - International Symposium on Biomedical Imaging - April 4, 2024 Category: Radiology Authors: Haotian Wang Min Xian Aleksandar Vakanski Bryar Shareef Source Type: research

Enhanced sharp-gan for histopathology image synthesis
Proc IEEE Int Symp Biomed Imaging. 2023 Apr;2023:10.1109/isbi53787.2023.10230516. doi: 10.1109/isbi53787.2023.10230516. Epub 2023 Sep 1.ABSTRACTHistopathology image synthesis aims to address the data shortage issue in training deep learning approaches for accurate cancer detection. However, existing methods struggle to produce realistic images that have accurate nuclei boundaries and less artifacts, which limits the application in downstream tasks. To address the challenges, we propose a novel approach that enhances the quality of synthetic images by using nuclei topology and contour regularization. The proposed approach u...
Source: Proceedings - International Symposium on Biomedical Imaging - April 4, 2024 Category: Radiology Authors: Sujata Butte Haotian Wang Aleksandar Vakanski Min Xian Source Type: research

Sian: style-guided instance-adaptive normalization for multi-organ histopathology image synthesis
Proc IEEE Int Symp Biomed Imaging. 2023 Apr;2023:10.1109/isbi53787.2023.10230507. doi: 10.1109/isbi53787.2023.10230507. Epub 2023 Sep 1.ABSTRACTExisting deep neural networks for histopathology image synthesis cannot generate image styles that align with different organs, and cannot produce accurate boundaries of clustered nuclei. To address these issues, we propose a style-guided instance-adaptive normalization (SIAN) approach to synthesize realistic color distributions and textures for histopathology images from different organs. SIAN contains four phases, semantization, stylization, instantiation, and modulation. The fir...
Source: Proceedings - International Symposium on Biomedical Imaging - April 4, 2024 Category: Radiology Authors: Haotian Wang Min Xian Aleksandar Vakanski Bryar Shareef Source Type: research

Enhanced sharp-gan for histopathology image synthesis
Proc IEEE Int Symp Biomed Imaging. 2023 Apr;2023:10.1109/isbi53787.2023.10230516. doi: 10.1109/isbi53787.2023.10230516. Epub 2023 Sep 1.ABSTRACTHistopathology image synthesis aims to address the data shortage issue in training deep learning approaches for accurate cancer detection. However, existing methods struggle to produce realistic images that have accurate nuclei boundaries and less artifacts, which limits the application in downstream tasks. To address the challenges, we propose a novel approach that enhances the quality of synthetic images by using nuclei topology and contour regularization. The proposed approach u...
Source: Proceedings - International Symposium on Biomedical Imaging - April 4, 2024 Category: Radiology Authors: Sujata Butte Haotian Wang Aleksandar Vakanski Min Xian Source Type: research

Sian: style-guided instance-adaptive normalization for multi-organ histopathology image synthesis
Proc IEEE Int Symp Biomed Imaging. 2023 Apr;2023:10.1109/isbi53787.2023.10230507. doi: 10.1109/isbi53787.2023.10230507. Epub 2023 Sep 1.ABSTRACTExisting deep neural networks for histopathology image synthesis cannot generate image styles that align with different organs, and cannot produce accurate boundaries of clustered nuclei. To address these issues, we propose a style-guided instance-adaptive normalization (SIAN) approach to synthesize realistic color distributions and textures for histopathology images from different organs. SIAN contains four phases, semantization, stylization, instantiation, and modulation. The fir...
Source: Proceedings - International Symposium on Biomedical Imaging - April 4, 2024 Category: Radiology Authors: Haotian Wang Min Xian Aleksandar Vakanski Bryar Shareef Source Type: research

Enhanced sharp-gan for histopathology image synthesis
Proc IEEE Int Symp Biomed Imaging. 2023 Apr;2023:10.1109/isbi53787.2023.10230516. doi: 10.1109/isbi53787.2023.10230516. Epub 2023 Sep 1.ABSTRACTHistopathology image synthesis aims to address the data shortage issue in training deep learning approaches for accurate cancer detection. However, existing methods struggle to produce realistic images that have accurate nuclei boundaries and less artifacts, which limits the application in downstream tasks. To address the challenges, we propose a novel approach that enhances the quality of synthetic images by using nuclei topology and contour regularization. The proposed approach u...
Source: Proceedings - International Symposium on Biomedical Imaging - April 4, 2024 Category: Radiology Authors: Sujata Butte Haotian Wang Aleksandar Vakanski Min Xian Source Type: research

Sian: style-guided instance-adaptive normalization for multi-organ histopathology image synthesis
Proc IEEE Int Symp Biomed Imaging. 2023 Apr;2023:10.1109/isbi53787.2023.10230507. doi: 10.1109/isbi53787.2023.10230507. Epub 2023 Sep 1.ABSTRACTExisting deep neural networks for histopathology image synthesis cannot generate image styles that align with different organs, and cannot produce accurate boundaries of clustered nuclei. To address these issues, we propose a style-guided instance-adaptive normalization (SIAN) approach to synthesize realistic color distributions and textures for histopathology images from different organs. SIAN contains four phases, semantization, stylization, instantiation, and modulation. The fir...
Source: Proceedings - International Symposium on Biomedical Imaging - April 4, 2024 Category: Radiology Authors: Haotian Wang Min Xian Aleksandar Vakanski Bryar Shareef Source Type: research

Enhanced sharp-gan for histopathology image synthesis
Proc IEEE Int Symp Biomed Imaging. 2023 Apr;2023:10.1109/isbi53787.2023.10230516. doi: 10.1109/isbi53787.2023.10230516. Epub 2023 Sep 1.ABSTRACTHistopathology image synthesis aims to address the data shortage issue in training deep learning approaches for accurate cancer detection. However, existing methods struggle to produce realistic images that have accurate nuclei boundaries and less artifacts, which limits the application in downstream tasks. To address the challenges, we propose a novel approach that enhances the quality of synthetic images by using nuclei topology and contour regularization. The proposed approach u...
Source: Proceedings - International Symposium on Biomedical Imaging - April 4, 2024 Category: Radiology Authors: Sujata Butte Haotian Wang Aleksandar Vakanski Min Xian Source Type: research

Sian: style-guided instance-adaptive normalization for multi-organ histopathology image synthesis
Proc IEEE Int Symp Biomed Imaging. 2023 Apr;2023:10.1109/isbi53787.2023.10230507. doi: 10.1109/isbi53787.2023.10230507. Epub 2023 Sep 1.ABSTRACTExisting deep neural networks for histopathology image synthesis cannot generate image styles that align with different organs, and cannot produce accurate boundaries of clustered nuclei. To address these issues, we propose a style-guided instance-adaptive normalization (SIAN) approach to synthesize realistic color distributions and textures for histopathology images from different organs. SIAN contains four phases, semantization, stylization, instantiation, and modulation. The fir...
Source: Proceedings - International Symposium on Biomedical Imaging - April 4, 2024 Category: Radiology Authors: Haotian Wang Min Xian Aleksandar Vakanski Bryar Shareef Source Type: research

Enhanced sharp-gan for histopathology image synthesis
Proc IEEE Int Symp Biomed Imaging. 2023 Apr;2023:10.1109/isbi53787.2023.10230516. doi: 10.1109/isbi53787.2023.10230516. Epub 2023 Sep 1.ABSTRACTHistopathology image synthesis aims to address the data shortage issue in training deep learning approaches for accurate cancer detection. However, existing methods struggle to produce realistic images that have accurate nuclei boundaries and less artifacts, which limits the application in downstream tasks. To address the challenges, we propose a novel approach that enhances the quality of synthetic images by using nuclei topology and contour regularization. The proposed approach u...
Source: Proceedings - International Symposium on Biomedical Imaging - April 4, 2024 Category: Radiology Authors: Sujata Butte Haotian Wang Aleksandar Vakanski Min Xian Source Type: research

Sian: style-guided instance-adaptive normalization for multi-organ histopathology image synthesis
Proc IEEE Int Symp Biomed Imaging. 2023 Apr;2023:10.1109/isbi53787.2023.10230507. doi: 10.1109/isbi53787.2023.10230507. Epub 2023 Sep 1.ABSTRACTExisting deep neural networks for histopathology image synthesis cannot generate image styles that align with different organs, and cannot produce accurate boundaries of clustered nuclei. To address these issues, we propose a style-guided instance-adaptive normalization (SIAN) approach to synthesize realistic color distributions and textures for histopathology images from different organs. SIAN contains four phases, semantization, stylization, instantiation, and modulation. The fir...
Source: Proceedings - International Symposium on Biomedical Imaging - April 4, 2024 Category: Radiology Authors: Haotian Wang Min Xian Aleksandar Vakanski Bryar Shareef Source Type: research

Enhanced sharp-gan for histopathology image synthesis
Proc IEEE Int Symp Biomed Imaging. 2023 Apr;2023:10.1109/isbi53787.2023.10230516. doi: 10.1109/isbi53787.2023.10230516. Epub 2023 Sep 1.ABSTRACTHistopathology image synthesis aims to address the data shortage issue in training deep learning approaches for accurate cancer detection. However, existing methods struggle to produce realistic images that have accurate nuclei boundaries and less artifacts, which limits the application in downstream tasks. To address the challenges, we propose a novel approach that enhances the quality of synthetic images by using nuclei topology and contour regularization. The proposed approach u...
Source: Proceedings - International Symposium on Biomedical Imaging - April 4, 2024 Category: Radiology Authors: Sujata Butte Haotian Wang Aleksandar Vakanski Min Xian Source Type: research

Sian: style-guided instance-adaptive normalization for multi-organ histopathology image synthesis
Proc IEEE Int Symp Biomed Imaging. 2023 Apr;2023:10.1109/isbi53787.2023.10230507. doi: 10.1109/isbi53787.2023.10230507. Epub 2023 Sep 1.ABSTRACTExisting deep neural networks for histopathology image synthesis cannot generate image styles that align with different organs, and cannot produce accurate boundaries of clustered nuclei. To address these issues, we propose a style-guided instance-adaptive normalization (SIAN) approach to synthesize realistic color distributions and textures for histopathology images from different organs. SIAN contains four phases, semantization, stylization, instantiation, and modulation. The fir...
Source: Proceedings - International Symposium on Biomedical Imaging - April 4, 2024 Category: Radiology Authors: Haotian Wang Min Xian Aleksandar Vakanski Bryar Shareef Source Type: research