Quantification of Tomographic Patterns associated with COVID-19 from Chest CT. - Shikha Chaganti; Abishek Balachandran; Guillaume Chabin; Stuart Cohen; Thomas Flohr 001; Bogdan Georgescu; Philippe Grenier; Sasa Grbic; Siqi Liu 001; François Mellot; Nicolas Murray; Savvas Nicolaou; et al. (CoRR, 2020)

3D Tomographic Pattern Synthesis for Enhancing the Quantification of COVID-19. - Siqi Liu 001; Bogdan Georgescu; Zhoubing Xu; Youngjin Yoo; Guillaume Chabin; Shikha Chaganti; Sasa Grbic; Sebastian Piat; Brian Teixeira; Abishek Balachandran; Vishwanath RS; Thomas J. Re; et al. (CoRR, 2020)

Automated detection and quantification of COVID-19 airspace disease on chest radiographs: A novel approach achieving radiologist-level performance using a CNN trained on digital reconstructed radiographs (DRRs) from CT-based ground-truth. - Eduardo Jose Mortani Barbosa Jr.; Warren B. Gefter; Rochelle Yang; Florin C. Ghesu; Siqi Liu 001; Boris Mailhé; Awais Mansoor; Sasa Grbic; Sebastian Piat; Guillaume Chabin; R. S. Vishwanath; Abishek Balachandran; et al. (CoRR, 2020)

Brain midline shift detection and quantification by a cascaded deep network pipeline on non-contrast computed tomography scans. - Nguyen P. Nguyen; Youngjin Yoo; Andrei Chekkoury; Eva Eibenberger; Thomas J. Re; Jyotipriya Das; Abishek Balachandran; Yvonne W. Lui; Pina C. Sanelli; Thomas J. Schroeppel; Uttam Bodanapally; Savvas Nicolaou; et al. (ICCVW, 2021)

Quantifying and leveraging predictive uncertainty for medical image assessment. - Florin C. Ghesu; Bogdan Georgescu; Awais Mansoor; Youngjin Yoo; Eli Gibson; R. S. Vishwanath; Abishek Balachandran; James M. Balter; Yue Cao; Ramandeep Singh; Subba R. Digumarthy; Mannudeep K. Kalra; et al. (Medical Image Anal., 2021)

Multi-scale Self-Supervised Learning for Longitudinal Lesion Tracking with Optional Supervision. - Anamaria Vizitiu; Antonia T. Mohaiu; Ioan M. Popdan; Abishek Balachandran; Florin C. Ghesu; Dorin Comaniciu (MICCAI (1), 2023)