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Quantification of Tomographic Patterns associated with COVID-19 from Chest CT., , , , , , , , , and 10 other author(s). 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., , , , , , , , , and 6 other author(s). CoRR, (2020)Brain midline shift detection and quantification by a cascaded deep network pipeline on non-contrast computed tomography scans., , , , , , , , , and 6 other author(s). ICCVW, page 487-495. IEEE, (2021)Quantifying and Leveraging Predictive Uncertainty for Medical Image Assessment., , , , , , , , , and 4 other author(s). CoRR, (2020)Multi-scale Self-Supervised Learning for Longitudinal Lesion Tracking with Optional Supervision., , , , , and . MICCAI (1), volume 14220 of Lecture Notes in Computer Science, page 573-582. Springer, (2023)Quantifying and leveraging predictive uncertainty for medical image assessment., , , , , , , , , and 4 other author(s). Medical Image Anal., (2021)3D Tomographic Pattern Synthesis for Enhancing the Quantification of COVID-19., , , , , , , , , and 3 other author(s). CoRR, (2020)