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Anomaly detection through latent space restoration using vector-quantized variational autoencoders.

, and . CoRR, (2020)

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Deep Learning for Cardiac Image Segmentation: A Review, , , , , , and . Front. Cardiovasc. Med., (March 2020)Harder synthetic anomalies to improve OoD detection in Medical Images., and . CoRR, (2023)Explainable Anatomical Shape Analysis Through Deep Hierarchical Generative Models., , , , , , , , , and 5 other author(s). IEEE Trans. Medical Imaging, 39 (6): 2088-2099 (2020)NeSy4VRD: A Multifaceted Resource for Neurosymbolic AI Research using Knowledge Graphs in Visual Relationship Detection., , , and . CoRR, (2023)Sample selection with noise rate estimation in noise learning of medical image analysis., , and . CoRR, (2023)Deep learning for cardiac image segmentation: A review., , , , , , and . CoRR, (2019)Blissful Ignorance: Anti-Transfer Learning for Task Invariance., , and . CoRR, (2020)Explainable Shape Analysis through Deep Hierarchical Generative Models: Application to Cardiac Remodeling., , , , , , , , , and 4 other author(s). CoRR, (2019)A novel approach to motion correction for ASL images based on brain contours., , , , , and . Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 9417 of SPIE Proceedings, page 94171U. SPIE, (2015)Anomaly Detection Through Latent Space Restoration Using Vector Quantized Variational Autoencoders., and . ISBI, page 1764-1767. IEEE, (2021)