Extending the value of routine lung screening CT with quantitative body composition assessment
Nov. 28, 2022—Kaiwen Xu, Riqiang Gao, Yucheng Tang, Steve A. Deppen, Kim L. Sandler, Michael N. Kammer, Sanja L. Antic, Fabien Maldonado, Yuankai Huo, Mirza S. Khan, Bennett A. Landman Abstract Certain body composition phenotypes, like sarcopenia, are well established as predictive markers for post-surgery complications and overall survival of lung cancer patients. However, their association with...
SynBOLD-DisCo: Synthetic BOLD images for distortion correction of fMRI without additional calibration scans
Nov. 13, 2022—Tian Yu*, Leon Y. Cai*, Victoria L. Morgan, Sarah E. Goodale, Dario J. Englot, Catherine E. Chang, Bennett A. Landman, and Kurt G. Schilling * Equal first authorship https://github.com/MASILab/SynBOLD-DisCo Abstract The blood oxygen level dependent (BOLD) signal from functional magnetic resonance imaging (fMRI) is a noninvasive technique that has been widely used in research to...
Batch size: go big or go home? Counterintuitive improvement in medical autoencoders with smaller batch size
Nov. 13, 2022—Cailey I. Kerley*, Leon Y. Cai*, Yucheng Tang, Lori L. Beason-Held, Susan M. Resnick, Laurie E. Cutting, and Bennett A. Landman. *Equal first authorship Abstract Batch size is a key hyperparameter in training deep learning models. Conventional wisdom suggests larger batches produce improved model performance. Here we present evidence to the contrary, particularly when using autoencoders...
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Transformer for Medical Image Segmentation”, arXiv 2022 Full Text Abstract Vision transformers (ViTs) have quickly superseded convolutional networks (ConvNets) as the current state-of-the-art (SOTA) models for medical image segmentation.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...
Integrating the BIDS Neuroimaging Data Format and Workflow Optimization for Large-Scale Medical Image Analysis
Aug. 3, 2022—Shunxing Bao, Brian D Boyd, Praitayini Kanakaraj, Karthik Ramadass, Francisco A. C. Meyer, Yuqian Liu, William E. Duett, Yuankai Huo, Ilwoo Lyu, David H. Zald, Seth A. Smith, Baxter P. Rogers, Bennett A. Landman. Integrating the BIDS Neuroimaging Data Format and Workflow Optimization for Large-Scale Medical Image Analysis. J Digit Imaging (2022). https://doi.org/10.1007/s10278-022-00679-8 Full Text Abstract A robust medical image computing...
The influence of regions of interest on tractography virtual dissection protocols: general principles to learn and to follow
Jul. 26, 2022—Rheault, Francois, Kurt G. Schilling, Sami Obaid, John P. Begnoche, Laurie E. Cutting, Maxime Descoteaux, Bennett A. Landman, and Laurent Petit. “The influence of regions of interest on tractography virtual dissection protocols: general principles to learn and to follow.” Brain Structure and Function (2022): 1-17. Full Text Abstract Purpose: Efficient communication across fields of research is challenging, especially...
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...
Workflow Integration of Research AI Tools into a Hospital Radiology Rapid Prototyping Environment
Jul. 25, 2022—Praitayini Kanakaraj, Karthik Ramadas, Shunxing Bao, Melissa Basford, Laura M. Jones, Ho Hin Lee, Kurt G. Schilling, John Jeffery Carr, James Gregory Terry, Yuankai Huo, Kim Lori Sandler, Allen T. Netwon, Bennett A. Landman “Workflow Integration of Research AI Tools into a Hospital Radiology Rapid Prototyping Environment”. Journal of Digital Imaging (2022): 1-11. Full Text...