SOURCE-LINKED INTELLIGENCE
Initialization and Stopping Tolerance in CPU Dermoscopic Segmentation
Contour initialization and numerical stopping can jointly affect the evaluation of active-contour segmentation. We examine their interaction using the open-source scikit-image Chan-Vese implementation on a resized ISIC 2017 mirror. A fixed development set of 100 images selects a common input channel; all 600 images in the repository's held-out partition are then evaluated. Otsu thresholding is compared with checkerboard-, disk-, and Otsu-initialized contours under default and tighter level-set tolerances. At the default tolerance, Otsu initialization increases mean image Dice from 0.6011 to 0.
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- arXiv · AI, language, vision and robotics · 2026-09-22T04:40:55.000Z
First collected: 2026-09-23T04:21:13.910Z. This is not the publication date.