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Routine clinical reports and historical scans can entirely replace manual voxel annotations, yielding dense tumor segmenters that outperform supervised public baselines at zero labeling cost.
Shrinking a 102M-parameter nnU-Net by 81× costs barely 2.5% in segmentation Dice while actually boosting lesion-level detection F1 by over 5 points.