Image Processing Category
Exploratory multi-site magnetic resonance spectroscopic imaging shows white matter neuroaxonal loss associated with complications of type 1 diabetes in children
Aug. 31, 2023—Cai LY, Tanase C, Anderson AW, Patel NJ, Lee CA, Jones RS, LeStourgeon LM, Mahon A, Taki I, Juvera J, Pruthi S, Gwal K, Ozturk A, Kang H, Rewers A, Rewers MJ, Alonso GT, Glaser N, Ghetti S, Jaser SS, Landman BA, Jordan LC Paper: https://pubmed.ncbi.nlm.nih.gov/37263786/ Abstract Background and purpose: Type 1 diabetes affects over 200,000...
AI Body Composition in Lung Cancer Screening: Added Value Beyond Lung Cancer Detection
Aug. 31, 2023—Kaiwen Xu, Mirza S. Khan, Thomas Z. Li, Riqiang Gao, James G. Terry, Yuankai Huo, Thomas A. Lasko, John Jeffrey Carr, Fabien Maldonado, Bennett A. Landman, Kim L. Sandler Paper: https://pubs.rsna.org/doi/epdf/10.1148/radiol.222937 Abstract Background An artificial intelligence (AI) algorithm has been developed for fully automated body composition assessment of lung cancer screening noncontrast low-dose CT of the...
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...
Efficient approximate signal reconstruction for correction of gradient nonlinearities in diffusion-weighted imaging
Aug. 31, 2023—Praitayini Kanakaraj, Leon Y. Cai, Tianyuan Yao, Francois Rheault, Baxter P. Rogers, Adam Anderson, Kurt G. Schilling, Bennett A. Landman. Magn Reson Imaging. 2023 Oct Full Text Abstract In diffusion weighted MRI (DW-MRI), hardware nonlinearities lead to spatial variations in the orientation and magnitude of diffusion weighting. While the correction of these spatial distortions has...
Mapping the impact of nonlinear gradient fields with noise on diffusion MRI
Aug. 31, 2023—Praitayini Kanakaraj, Leon Y. Cai, Francois Rheault, Fang-Cheng Yeh, Baxter P. Rogers, Kurt G. Schilling, Bennett A. Landman (2023). Mapping the impact of nonlinear gradient fields with noise on diffusion MRI. Magn Reson Imaging. 2023 May Full Text Abstract In diffusion MRI, gradient nonlinearities cause spatial variations in the magnitude and direction of diffusion gradients. Studies...
Convolutional-recurrent neural networks approximate diffusion tractography from T1-weighted MRI and associated anatomical context
May. 29, 2023—Leon Y. Cai, Ho Hin Lee, Nancy R. Newlin, Cailey I. Kerley, Praitayini Kanakaraj, Qi Yang, Graham W. Johnson, Daniel Moyer, Kurt G. Schilling, François Rheault, and Bennett A. Landman Paper: https://www.biorxiv.org/content/10.1101/2023.02.25.530046v2 Code: https://github.com/MASILab/cornn_tractography Abstract Diffusion MRI (dMRI) streamline tractography is the gold-standard for in vivo estimation of white matter (WM) pathways in the brain. However, the...
Implementation considerations for deep learning with diffusion MRI streamline tractography
May. 29, 2023—Leon Y. Cai, Ho Hin Lee, Nancy R. Newlin, Michael E. Kim, Daniel Moyer, Francois Rheault, Kurt G. Schilling, and Bennett A. Landman Paper: https://www.biorxiv.org/content/10.1101/2023.04.03.535465v1 Code: https://github.com/MASILab/STrUDeL Abstract One area of medical imaging that has recently experienced innovative deep learning advances is diffusion MRI (dMRI) streamline tractography with recurrent neural networks (RNNs). Unlike traditional imaging studies which...
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...
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...