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Single Slice Thigh CT Muscle Group Segmentation with Domain Adaptation and Self-Training

Aug. 31, 2023—Qi Yang, Xin Yu, Ho Hin Lee, Leon Y. Cai, Kaiwen Xu, Shunxing Bao, Yuankai Huo , Ann Zenobia Moore, Sokratis Makrogiannis, Luigi Ferrucci, Bennett A. Landman. Objective: Thigh muscle group segmentation is important for assessment of muscle anatomy, metabolic disease and aging. Many efforts have been put into quantifying muscle tissues with magnetic resonance...

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Label efficient segmentation of single slice thigh CT with two-stage pseudo labels

Jul. 25, 2022—Qi Yang, Xin Yu, Ho Hin Lee, Yucheng Tang, Shunxing Bao,Kristofer S. Gravenstein, Ann Zenobia Moore, Sokratis Makrogiannis, Luigi Ferrucci, and Bennett A. Landman. “Label efficient segmentation of single slice thigh CT with two-stage pseudo labels” Journal of Medical Imaging, 2022 Purpose: Muscle, bone, and fat segmentation from thigh images is essential for quantifying body...

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Reducing Positional Variance in Cross-sectional Abdominal CT Slices with Deep Conditional Generative Models

Jul. 25, 2022—Xin Yu*, Qi Yang*, Yucheng Tang, Riqiang Gao, Shunxing Bao, Leon Y. Cai, Ho Hin Lee, Ann Zenobia Moore, Luigi Ferrucci, Bennett A. Landman, “Reducing Positional Variance in Cross-sectional Abdominal CT Slices with Deep Conditional Generative Models”, MICCAI 2022   2D low-dose single-slice abdominal computed tomography (CT) slice enables direct measurements of body composition, which...

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Accelerating 2D Abdominal Organ Segmentation with Active Learning

Dec. 10, 2021—Xin Yu, Yucheng Tang, Qi Yang, Ho Hin Lee, Shunxing Bao, Ann Zenobia Moore, Luigi Ferrucci, Bennett A. Landman   Abdominal computed tomography CT imaging enables assessment of body habitus and organ health. Quantification of these health factors necessitates semantic segmentation of key structures. Deep learning efforts have shown remarkable success in automating segmentation of...

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Quantification of muscle, bones and fat on single slice thigh CT

Dec. 10, 2021—Qi Yang, Xin Yu, Ho Hin Lee, Yucheng Tang, Shunxing Bao, Kristofer S Gravenstein, Ann Zenobia Moore, Sokratis Makrogiannis ,Luigi Ferrucci , Bennett A Landman Abstract Muscle, bone, and fat segmentation of CT thigh slice is essential for body composition research. Voxel-wise image segmentation enables quantification of tissue properties including area, intensity and texture. Deep learning...

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Pandora: 4-D White Matter Bundle Population-Based Atlases Derived from Diffusion MRI Fiber Tractography

Nov. 29, 2020—Colin B. Hansen, Qi Yang,  Ilwoo Lyu, Francois Rheault, Cailey Kerley, Bramsh Qamar Chandio, Shreyas Fadnavis, Owen Williams, Andrea T. Shafer, Susan M. Resnick, David H. Zald, Laurie E. Cutting, Warren D. Taylor, Brian Boyd, Eleftherios Garyfallidis, Adam W. Anderson, Maxime Descoteaux, Bennett A. Landman, Kurt G. Schilling. Pandora: 4-D White Matter Bundle Population-Based Atlases Derived from Diffusion MRI Fiber Tractography. Neuroinform (2020). Full Text Abstract Brain atlases have proven to be valuable neuroscience tools for...

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