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Unsupervised anomaly detection of paranasal anomalies in the maxillary sinus., , , , , , , , , and 1 other author(s). Medical Imaging: Computer-Aided Diagnosis, volume 12465 of SPIE Proceedings, SPIE, (2023)Data Pooling and Sampling of Heterogeneous Image Data for White Matter Hyperintensity Segmentation., , , , , , , , , and . OR/MLCN@MICCAI, volume 11796 of Lecture Notes in Computer Science, page 86-94. Springer, (2019)Self-supervised learning for classifying paranasal anomalies in the maxillary sinus., , , , , , , , , and 2 other author(s). Int. J. Comput. Assist. Radiol. Surg., 19 (9): 1713-1721 (September 2024)MRI-Guided Thrombolysis for Stroke with Unknown Time of Onset, , , , , , , , , and 32 other author(s). New England Journal of Medicine, (May 16, 2018)Supervised Contrastive Learning to Classify Paranasal Anomalies in the Maxillary Sinus., , , , , , , , , and 3 other author(s). MICCAI (3), volume 13433 of Lecture Notes in Computer Science, page 429-438. Springer, (2022)