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December, 2020

RAP-Net: Coarse-to-Fine Multi-Organ Segmentation with Single Random Anatomical Prior

Dec. 28, 2020—Ho Hin Lee, Yucheng Tang, Shunxing Bao, Richard G. Abramson, Yuankai Huo, Bennett A. Landman. “RAP-Net: Coarse-to-Fine Multi-Organ Segmentation with Single Random Anatomical Prior.” arXiv preprint arXiv:2012.12425 (2020). Full Text Abstract Performing coarse-to-fine abdominal multi-organ segmentation facilitates to extract high-resolution segmentation minimizing the lost of spatial contextual information. However, current coarse-to-refine approaches require a significant number of models...

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Multi-Contrast Computed Tomography Healthy Kidney Atlas

Dec. 28, 2020—Ho Hin Lee, Yucheng Tang, Kaiwen Xu, Shunxing Bao, Agnes B. Fogo, Raymond Harris, Mark P. de Caestecker, Mattias Heinrich, Jeffery M. Spraggins, Yuankai Huo, Bennett A. Landman, “Multi-Contrast Computed Tomography Healthy Kidney Atlas.” arXiv preprint arXiv:2012.12432 (2020). Full Text Abstract The construction of three-dimensional multi-modal tissue maps provides an opportunity to spur interdisciplinary innovations across temporal and...

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Challenges for biophysical modeling of microstructure

Dec. 9, 2020—Ileana O. Jelescu, Marco Palombo, Francesca Bagnato, Kurt G. Schilling. “Challenges for biophysical modeling of microstructure”. (2020) Journal of Neuroscience Methods 108861. Full text: https: https://www.sciencedirect.com/science/article/pii/S0165027020302843 Abstract The biophysical modeling efforts in diffusion MRI have grown considerably over the past 25 years. In this review, we dwell on the various challenges along the journey of...

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Prediction of Type II Diabetes Onset with Computed Tomography and Electronic Medical Records

Dec. 7, 2020—Yucheng Tang, Riqiang Gao, Ho Hin Lee, Quinn Stanton Wells, Ashley Spann, James Gregory Terry, Jeff Carr, Yuankai Huo, Shunxing Bao and Bennett A. Landman, “Prediction of Type II Diabetes Onset with Computed Tomography and Electronic Medical Records”, MICCAI CLIP, 2020. Full Text: Abstract Type II diabetes mellitus (T2DM) is a significant public health concern...

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Learning from dispersed manual annotations with an optimized data weighting policy

Dec. 7, 2020—Yucheng Tang, Riqiang Gao, Yunqiang Chen, Dashan Gao, Michael R. Savona, Richard G. Abramson, Shunxing Bao, Yuankai Huo and Bennett A. Landman, “Learning from Dispersed Manual Annotations with an Optimized Data Weighting Policy”, Journal of Medical Imaging, 2020. Full Text: Abstract https://pubmed.ncbi.nlm.nih.gov/32775501/ Purpose: Deep learning methods have become essential tools for quantitative interpretation of medical...

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Construction of a Multi-Phase Contrast Computed Tomography Kidney Atlas

Dec. 6, 2020—Ho Hin Lee, Yucheng Tang, Kaiwen Xu, Shunxing Bao, Agnes B. Fogo, Raymond Harris, Mark P. de Caestecker, Mattias Heinrich, Jeffrey Spraggins, Yuankai Huo, Bennett A, Landman, Construction of a Multi-Phase Contrast Computed Tomography Kidney Atlas, SPIE 2021 Medical Imaging Full Text Abstract The Human BioMolecular Atlas Program (HuBMAP) seeks to create a molecular atlas at the cellular level of...

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A cross-platform informatics system for the Gut Cell Atlas: integrating from clinical, anatomical and histological data

Dec. 6, 2020—Shunxing Bao, Sophie Chiron, Yucheng Tang, Cody N. Heiser, Austin N. Southard-Smith, Ho Hin Lee, Marisol A. Ramirez, Yuankai Huo, Mary K. Washington, Elizabeth A. Scoville, Joseph T. Roland, Qi Liu, Ken S. Lau, Keith T. Wilson, Lori A. Coburn, Bennett A. Landman, A cross-platform informatics system for the Gut Cell Atlas: integrating from clinical,...

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Establishing Surface Correspondence for Post-surgical Cortical Thickness Changes in Temporal Lobe Epilepsy

Dec. 5, 2020—Yue Liu, Dario J. Englot, Victoria L. Morgan, Warren D. Taylor, Ying Wei, Ipek Oguz, Bennett A. Landman, Ilwoo Lyu. Establishing Surface Correspondence for Post-surgical Cortical Thickness Changes in Temporal Lobe Epilepsy. SPIE Medical Imaging, 2021. Full Text Abstract In pre- and post-surgical surface shape analysis, establishing shape correspondence is necessary to investigate the post-operative...

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Semi-supervised Machine Learning with MixMatch and Equivalence Classes

Dec. 4, 2020—Colin B. Hansen, Vishwesh Nath, Riqiang Gao, Camilo Bermudez, Yuankai Huo, Kim L. Sandler, Pierre P. Massion, Jeffrey D. Blume, Thomas A. Lasko, Bennett A. Landman “Semi-supervised Machine Learning with MixMatch and Equivalence Classes.” Interpretable and Annotation-Efficient Learning for Medical Image Computing. Springer, Cham, 2020. 112-121. Full Text Abstract Semi-supervised methods have an increasing impact on...

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