SOURCE-LINKED INTELLIGENCE
BiCC: Bidirectional Connected-Component Loss for Instance-Aware Segmentation
Common segmentation losses aggregate errors voxel-wise, so lesions influence the objective in proportion to their volume, giving small but clinically critical lesions disproportionately little weight. Instance-aware losses aim to address this mismatch by assigning each lesion its own term. However, blob loss and CC-DiceCE derive their regions solely from annotations, so false-positive components receive no instance-level term. This matters in computer-assisted review, where each false-positive component may require separate inspection, making precision and false-positive burden important along
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-24T17:48:31.000Z
First collected: 2026-09-25T06:12:46.948Z. This is not the publication date.