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Bayesian QuickNAT: Model Uncertainty in Deep Whole-Brain Segmentation for Structure-wise Quality Control., , , and . CoRR, (2018)Recalibrating Fully Convolutional Networks With Spatial and Channel "Squeeze and Excitation" Blocks., , and . IEEE Trans. Medical Imaging, 38 (2): 540-549 (2019)Generative models improve fairness of medical classifiers under distribution shifts., , , , , , , , , and 2 other author(s). CoRR, (2023)Evaluating AI systems under uncertain ground truth: a case study in dermatology., , , , , , , , , and 10 other author(s). CoRR, (2023)Data Augmentation with Manifold Exploring Geometric Transformations for Increased Performance and Robustness., , , , , , and . CoRR, (2019)Robust and Efficient Medical Imaging with Self-Supervision., , , , , , , , , and 24 other author(s). CoRR, (2022)MINT: A wrapper to make multi-modal and multi-image AI models interactive., , , , , , , , , and 3 other author(s). CoRR, (2024)'Project & Excite' Modules for Segmentation of Volumetric Medical Scans., , , , and . MICCAI (2), volume 11765 of Lecture Notes in Computer Science, page 39-47. Springer, (2019)Manifold Exploring Data Augmentation with Geometric Transformations for Increased Performance and Robustness., , , , , and . IPMI, volume 11492 of Lecture Notes in Computer Science, page 517-529. Springer, (2019)Recalibrating Fully Convolutional Networks with Spatial and Channel 'Squeeze & Excitation' Blocks., , and . CoRR, (2018)