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Bern University Hospital University of Bern
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Self-supervised learning transforms cardiac CT analysis, achieving unprecedented segmentation accuracy and efficiency with the largest expert-annotated dataset to date.
Annotation noise in vascular CT scans can be detected with a novel method that reveals systematic biases, improving training robustness dramatically.
MIMFlow achieves a 32.8% performance boost over standard Normalizing Flows by cleverly decoupling low-frequency and high-frequency image generation tasks.
