Image Segmentation Category
Body Composition Assessment with Limited Field-of-view Computed Tomography: A Semantic Image Extension Perspective. Medical Image Analysis
Aug. 31, 2023—Kaiwen Xu, Thomas Li, Mirza S. Khan, Riqiang Gao, Sanja L. Antic, Yuankai Huo, Kim L. Sandler, Fabien Maldonado, Bennett A. Landman Paper: https://www.sciencedirect.com/science/article/pii/S1361841523001123 Code: https://github.com/MASILab/S-EFOV Abstract Field-of-view (FOV) tissue truncation beyond the lungs is common in routine lung screening computed tomography (CT). This poses limitations for opportunistic CT-based body composition (BC) assessment as key anatomical structures...
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...
UNesT: Local Spatial Representation Learning with Hierarchical Transformer for Efficient Medical Segmentation
Aug. 31, 2023—Xin Yu, Qi Yang, Yinchi Zhou, Leon Y. Cai , Riqiang Gao, Ho Hin Lee, Thomas Li, Shunxing Bao, Zhoubing Xu, Thomas A. Lasko, Richard G. Abramson, Zizhao Zhang, Yuankai Huo, Bennett A. Landman, Yucheng Tang Paper: https://arxiv.org/abs/2209.14378 Code: https://github.com/Project-MONAI/model-zoo/tree/dev/models Abstract Transformer-based models, capable of learning better global dependencies, have recently demonstrated exceptional repre- sentation learning capabilities...
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Transformer for Medical Image Segmentation”, arXiv 2022 Full Text Abstract Vision transformers (ViTs) have quickly superseded convolutional networks (ConvNets) as the current state-of-the-art (SOTA) models for medical image segmentation.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...
Generalizing deep learning brain segmentation for skull removal and intracranial measurements
Jul. 25, 2022—Yue Liu, Yuankai Huo, Blake Dewey, Ying Wei, Ilwoo Lyu, Bennett A. Landman ,“Generalizing deep learning brain segmentation for skull removal and intracranial measurements.”Magnetic Resonance Imaging. Volume 88, May 2022, Pages 44-52 Full Text Abstract Total intracranial volume (TICV) and posterior fossa volume (PFV) are essential covariates for brain volumetric analyses with structural magnetic resonanceimaging...
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...
Multimodal neuroimaging in pediatric type 1 diabetes: a pilot multisite feasibility study of acquisition quality, motion, and variability
Dec. 10, 2021—Leon Y. Cai, Costin Tanase, Adam W. Anderson, Karthik Ramadass, Francois Rheault, Chelsea A. Lee, Niral J. Patel, Sky Jones, Lauren M. LeStourgeon, Alix Mahon, Sumit Pruthi, Kriti Gwal, Arzu Ozturk, Hakmook Kang, Nicole Glaser, Simona Ghetti, Sarah S. Jaser, Lori C. Jordan, and Bennett A. Landman Abstract Type 1 diabetes (T1D) affects over 200,000...
TractEM: Evaluation of protocols for deterministic tractography white matter atlas
Dec. 3, 2021—Rheault, Francois, Roza G. Bayrak, Xuan Wang, Kurt G. Schilling, Jasmine M. Greer, Colin B. Hansen, Cailey Kerley et al. “TractEM: Evaluation of protocols for deterministic tractography white matter atlas.” Magnetic Resonance Imaging 85 (2022): 44-56. Full Text Abstract Purpose: One of the key challenges of the manual delineation of white matter pathways is human-rater’s subjectivity in labeling....
Automated, open-source segmentation of the Hippocampus and amygdala with the open Vanderbilt archive of the temporal lobe
Aug. 28, 2021—Plassard, Andrew J., Shunxing Bao*, Maureen McHugo, Lori Beason-Held, Jennifer U. Blackford, Stephan Heckers, and Bennett A. Landman. “Automated, open-source segmentation of the Hippocampus and amygdala with the open Vanderbilt archive of the temporal lobe.” Magnetic Resonance Imaging 81 (2021): 17-23. Full text: https://www.sciencedirect.com/science/article/abs/pii/S0730725X21000692 Abstract Examining volumetric differences of the amygdala and anterior-posterior regions of the...
Generalizing deep whole-brain segmentation for post-contrast MRI with transfer learning
Dec. 26, 2020—Bermudez, C., Remedios, S. W., Ramadass, K., McHugo, M., Heckers, S., Huo, Y., & Landman, B. A. (2020). Generalizing deep whole-brain segmentation for post-contrast MRI with transfer learning. Journal of Medical Imaging, 7(6), 064004. Full Text: https://pubmed.ncbi.nlm.nih.gov/33381612/ Abstract Purpose: Generalizability is an important problem in deep neural networks, especially with variability of data acquisition in...