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Adversarial Image Synthesis for Unpaired Multi-modal Cardiac Data.

, , , and . SASHIMI@MICCAI, volume 10557 of Lecture Notes in Computer Science, page 3-13. Springer, (2017)

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Deep Learning-Based Segmentation and Uncertainty Assessment for Automated Analysis of Myocardial Perfusion MRI Datasets Using Patch-Level Training and Advanced Data Augmentation., , , , , and . EMBC, page 4072-4078. IEEE, (2021)Temporal Uncertainty Localization to Enable Human-in-the-Loop Analysis of Dynamic Contrast-Enhanced Cardiac MRI Datasets., , , , , , and . MICCAI (3), volume 14222 of Lecture Notes in Computer Science, page 453-462. Springer, (2023)Disentangle, align and fuse for multimodal and zero-shot image segmentation., , , , , , and . CoRR, (2019)Unveiling Fairness Biases in Deep Learning-Based Brain MRI Reconstruction., , , and . CLIP/FAIMI/EPIMI@MICCAI, volume 14242 of Lecture Notes in Computer Science, page 102-111. Springer, (2023)Multimodal Cardiac Segmentation Using Disentangled Representation Learning., , , , , , , and . STACOM@MICCAI, volume 12009 of Lecture Notes in Computer Science, page 128-137. Springer, (2019)Semi-supervised Pathology Segmentation with Disentangled Representations., , , , , , , , and . DART/DCL@MICCAI, volume 12444 of Lecture Notes in Computer Science, page 62-72. Springer, (2020)Adversarial Image Synthesis for Unpaired Multi-modal Cardiac Data., , , and . SASHIMI@MICCAI, volume 10557 of Lecture Notes in Computer Science, page 3-13. Springer, (2017)Disentangle, Align and Fuse for Multimodal and Semi-Supervised Image Segmentation., , , , , , and . IEEE Trans. Medical Imaging, 40 (3): 781-792 (2021)A Patch-Wise Deep Learning Approach for Myocardial Blood Flow Quantification with Robustness to Noise and Nonrigid Motion., , , , , , and . EMBC, page 4045-4051. IEEE, (2021)Disentangled representation learning in cardiac image analysis., , , , , , , and . Medical Image Anal., (2019)