Extended Data Fig. 1: Examples of polyp segmentation on challenging samples.

Qualitative comparison of nine state-of-the-art segmentation models (columns, model names at bottom) on various colonoscopy images (top row). The second row displays the ground truth segmentations (expert annotation). The fourth row shows the baseline performance of each model (w/o EndoKED pre-training). The fifth row shows the performance of the same models after pre-training with the proposed distilled annotations (with EndoKED pre-training). The pre-trained models consistently produce more accurate and robust segmentation masks that are closer to the expert annotations, with fewer false positives and artifacts. The third row shows the output of the EndoKEG-SEG model for reference.