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Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark
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A single INR can now model complex, periodic deformations across entire image sequences, enabling self-regularization and outperforming prior methods.
A new dataset reveals that established segmentation methods can vary significantly in performance based on clinical context, challenging the notion of a one-size-fits-all metric.
Leveraging anatomical context can transform ambiguous pericardium segmentations into high-precision results, even from weak initial inputs.