SOURCE-LINKED INTELLIGENCE
Bayesian-Optimized Superpixel-GrabCut for Traceable Optic Disc Segmentation
Optic disc (OD) segmentation is essential for diagnosing ophthalmic pathologies from retinal fundus images. However, prevailing deep learning approaches operate as opaque black boxes, lacking the inference-stage mathematical traceability--a critical requirement for algorithmic auditing and failure analysis in clinical workflows. This paper presents a fully algorithmically traceable and trainable segmentation pipeline that jointly combines superpixel decomposition, hybrid brightness-proximity superpixel scoring, morphological regularization, iterative GrabCut refinement, and elliptical shape fi
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-29T11:09:59.000Z
First collected: 2026-09-21T07:51:58.603Z. This is not the publication date.