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STructural Rectal Atlas Deformation (StRAD) Features for Characterizing Intra- and Peri-wall Chemoradiation Response on MRI., , , , , , , and . MICCAI (4), volume 11767 of Lecture Notes in Computer Science, page 611-619. Springer, (2019)Radiomic characterization of perirectal fat on MRI enables accurate assessment of tumor regression and lymph node metastasis in rectal cancers after chemoradiation., , , , , , , , , and 2 other author(s). Medical Imaging: Image-Guided Procedures, volume 10951 of SPIE Proceedings, page 109512A. SPIE, (2019)Sparse Wavelet Networks., , , and . IEEE Signal Process. Lett., (2020)Region-specific fully convolutional networks for segmentation of the rectal wall on post-chemoradiation T2w MRI., , , , , , , and . Medical Imaging: Image-Guided Procedures, volume 10951 of SPIE Proceedings, page 1095134. SPIE, (2019)Residual Wavelon Convolutional Networks for Characterization of Disease Response on MRI., , , , and . MICCAI (3), volume 13433 of Lecture Notes in Computer Science, page 366-375. Springer, (2022)Identifying radiomic features associated with disease activity, patient outcomes, and serum phenotypes in pediatric Crohn's disease via MRI., , , , , and . Medical Imaging: Image-Guided Procedures, volume 12034 of SPIE Proceedings, SPIE, (2022)Integrating multi-plane and multi-region radiomic features to predict pathologic response to neoadjuvant chemoradiation in rectal cancers via pre-treatment MRI., , , , , , , , , and 7 other author(s). Medical Imaging: Image-Guided Procedures, volume 12466 of SPIE Proceedings, SPIE, (2023)Integrating radiomic features from T2-weighted and contrast-enhanced MRI to evaluate pathologic rectal tumor regression after chemoradiation., , , , , , , , , and 2 other author(s). Medical Imaging: Image-Guided Procedures, volume 10951 of SPIE Proceedings, page 109512R. SPIE, (2019)MRQy: An Open-Source Tool for Quality Control of MR Imaging Data., , , , , , , and . CoRR, (2020)CohortFinder: an open-source tool for data-driven partitioning of biomedical image cohorts to yield robust machine learning models., , , , , , , , , and 3 other author(s). CoRR, (2023)