Skip to main content

News Category

Time-distance vision transformers in lung cancer diagnosis from longitudinal computed tomography.

Dec. 2, 2022—Thomas Z. Li, Kaiwen Xu, Riqiang Gao, Yucheng Tang, Thomas A. Lasko, Fabien Maldonado, Kim Sandler, Bennett A. Landman. Time-distance vision transformers in lung cancer diagnosis from longitudinal computed tomography. SPIE Medical Imaging 2022. Full text: arxiv.org/abs/2209.01676 Abstract Features learned from single radiologic images are unable to provide information about whether and how much a lesion...

Read more


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...

Read more


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...

Read more


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...

Read more


Tractostorm 2: Optimizing tractography dissection reproducibility with segmentation protocol dissemination

Feb. 11, 2022—Rheault, Francois, Kurt G. Schilling, Alex Valcourt-Caron, Antoine Théberge, Charles Poirier, Gabrielle Grenier, Guido I. Guberman, John Begnoche, Jon Haitz Legarreta, Leon Y. Cai, Maggie Roy, Manon Edde, Marco Perez Caceres, Mario Ocampo-Pineda, Noor Al-Sharif, Philippe Karan, Pietro Bontempi, Sami Obaid, Sara Bosticardo, Simona Schiavi, Viljami Sairanen, Alessandro Daducci, Laurie E. Cutting, Laurent Petit, Maxime...

Read more


pyPheWAS: A Phenome-Disease Association Tool for Electronic Medical Record Analysis

Jan. 12, 2022—Kerley, C.I., Chaganti, S., Nguyen, T.Q. et al. pyPheWAS: A Phenome-Disease Association Tool for Electronic Medical Record Analysis. Neuroinform (2022). https://doi.org/10.1007/s12021-021-09553-4 Full text: NIHMSID, Springer Abstract Along with the increasing availability of electronic medical record (EMR) data, phenome-wide association studies (PheWAS) and phenome-disease association studies (PheDAS) have become a prominent, first-line method of analysis for uncovering...

Read more


Mapping the impact of non-linear gradient fields on diffusion MRI tensor estimation

Dec. 11, 2021—Praitayini Kanakaraj, Colin B. Hansen, Francois Rheault, Leon Y. Cai, Baxter P. Rogers, Kurt G. Schilling and Bennett A. Landman. “Mapping the impact of non-linear gradient fields on diffusion MRI tensor estimation”. SPIE Medical Imaging 2022. Accepted. Full Text Abstract Non-linear gradients impact diffusion weighted (DW) MRI by corrupting the experimental setup and lead to problems during...

Read more


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...

Read more


RAP-Net: Coarse-to-Fine Multi-Organ Segmentation with Single Random Anatomical Prior

Dec. 28, 2020—Ho Hin Lee, Yucheng Tang, Shunxing Bao, Richard G. Abramson, Yuankai Huo, Bennett A. Landman. “RAP-Net: Coarse-to-Fine Multi-Organ Segmentation with Single Random Anatomical Prior.” arXiv preprint arXiv:2012.12425 (2020). Full Text Abstract Performing coarse-to-fine abdominal multi-organ segmentation facilitates to extract high-resolution segmentation minimizing the lost of spatial contextual information. However, current coarse-to-refine approaches require a significant number of models...

Read more


Semi-supervised Machine Learning with MixMatch and Equivalence Classes

Dec. 4, 2020—Colin B. Hansen, Vishwesh Nath, Riqiang Gao, Camilo Bermudez, Yuankai Huo, Kim L. Sandler, Pierre P. Massion, Jeffrey D. Blume, Thomas A. Lasko, Bennett A. Landman “Semi-supervised Machine Learning with MixMatch and Equivalence Classes.” Interpretable and Annotation-Efficient Learning for Medical Image Computing. Springer, Cham, 2020. 112-121. Full Text Abstract Semi-supervised methods have an increasing impact on...

Read more