Abdomen Imaging Category
Semantic-Aware Contrastive Learning for Multi-object Medical Image Segmentation
Aug. 31, 2023—Ho Hin Lee, Yucheng Tang, Qi Yang, Xin Yu, Leon Y. Cai, Lucas W. Remedios, Shunxing Bao, Bennett A. Landman, Yuankai Huo Paper: https://ieeexplore.ieee.org/document/10149329 Code: https://github.com/MASILab/DCC_CL Abstract Medical image segmentation, or computing voxel-wise semantic masks, is a fundamental yet challenging task in medical imaging domain. To increase the ability of encoder-decoder neural networks to perform this task...
3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation
Oct. 6, 2022—Ho Hin Lee, Shunxing Bao, Yuankai Huo, Bennett A. Landman, “3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation”, arXiv 2022 Full Text Abstract Vision transformers (ViTs) have quickly superseded convolutional networks (ConvNets) as the current state-of-the-art (SOTA) models for medical image segmentation. Hierarchical transformers (e.g., Swin Transformers) reintroduced several...
Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis
Jul. 25, 2022—Tang, Yucheng, Dong Yang, Wenqi Li, Holger R. Roth, Bennett Landman, Daguang Xu, Vishwesh Nath, and Ali Hatamizadeh. “Self-supervised pre-training of swin transformers for 3d medical image analysis.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 20730-20740. 2022. Full text: Abstract Vision Transformers (ViT)s have shown great performance in self-supervised...
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...
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...
Pancreas CT Segmentation by Predictive Phenotyping
Dec. 14, 2021—Y. Tang, R.Gao, H.H.Lee, Q.Yang, X.Yu,Y.Zhou, S.Bao, Y.Huo, J.Spraggins, J.Virostko, Z.Xu, B.A. Landman. “Pancreas CTSegmentation by Predictive Phenotyping”. International Conference on MedicalImage Computing and Computer Assisted Intervention(MICCAI), 2021 Full Text: https://link.springer.com/chapter/10.1007/978-3-030-87193-2_3 Abstract Pancreas CT segmentation offers promise at understanding the structural manifestation of metabolic conditions. To date, the medical primary record of conditions that impact...
High-resolution 3D abdominal segmentation with random patch network fusion
Dec. 14, 2021—Y. Tang,R.Gao,S.Han, Y.Chen, D.Gao, V.Nath, C.Bermudez, M.R. Savona, R.G. Abramson, S.Bao,I.Lyu, Y.Huo and B.A. Landman,“High-resolution 3D Abdominal Segmentation with Random PatchNetworkFusion”,Medical Image Analysis, 2021. Full Text: https://www.sciencedirect.com/science/article/pii/S1361841520302589 Abstract Deep learning for three dimensional (3D) abdominal organ segmentation on high-resolution computed to- mography (CT) is a challenging topic, in part due to the limited memory provide...
Inpainting Missing Tissue in Multiplexed Immunofluorescence Imaging
Dec. 10, 2021—Shunxing Bao, Yucheng Tang, Ho Hin Lee, Riqiang Gao, Qi Yang, Xin Yu, Sophie Chiron, Lori A. Coburn, Keith T. Wilson, Joseph T. Roland, Bennett A. Landman, Yuankai Huo. “Inpainting Missing Tissue in Multiplexed Immunofluorescence Imaging” Medical Imaging 2022: Digital and Computational Pathology. International Society for Optics and Photonics, accepted Full text: [TBD] Abstract Multiplex immunofluorescence (MxIF) is...
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...
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...