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An Exploration of 2D and 3D Deep Learning Techniques for Cardiac MR Image Segmentation., , , and . STACOM@MICCAI, volume 10663 of Lecture Notes in Computer Science, page 111-119. Springer, (2017)Right for the Wrong Reason: Can Interpretable ML Techniques Detect Spurious Correlations?, , and . MICCAI (2), volume 14221 of Lecture Notes in Computer Science, page 425-434. Springer, (2023)Benchmarking Dependence Measures to Prevent Shortcut Learning in Medical Imaging., , , , , and . CoRR, (2024)Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?, , , , , , , , , and 27 other author(s). IEEE Trans. Medical Imaging, 37 (11): 2514-2525 (2018)Benchmarking Retinal Blood Vessel Segmentation Models for Cross-Dataset and Cross-Disease Generalization., , , , and . CoRR, (2024)Self-Aligning Manifolds for Matching Disparate Medical Image Datasets., , , , , , , and . IPMI, volume 9123 of Lecture Notes in Computer Science, page 363-374. Springer, (2015)Learning to Segment Medical Images with Scribble-Supervision Alone., , , , , and . DLMIA/ML-CDS@MICCAI, volume 11045 of Lecture Notes in Computer Science, page 236-244. Springer, (2018)Inherently Interpretable Multi-Label Classification Using Class-Specific Counterfactuals., , , , and . MIDL, volume 227 of Proceedings of Machine Learning Research, page 937-956. PMLR, (2023)Visual Explanations for the Detection of Diabetic Retinopathy from Retinal Fundus Images., , , , , , , and . MICCAI (2), volume 13432 of Lecture Notes in Computer Science, page 539-549. Springer, (2022)Employing Weak Annotations for Medical Image Analysis Problems., , , , , , and . CoRR, (2017)