ESRVS: Extreme Semi-Supervised Retinal Vessel Segmentation with a Single Annotated Image
Learning from minimal human supervision is a long-standing goal in medical image analysis, where dense expert annotations are costly. We study retinal vessel segmentation in an extreme semi-supervised setting with one annotated image and a pool of unlabeled images. We propose ESRVS, which selects a representative reference image for manual annotation and transfers vessel cues using target-domain-adapted DINOv3 features. ESRVS constructs a multi granular vessel prototype, combines prototype-simil
Record details
Published: 27 July 2026
Source: arXiv cs.AI
Category: Research
Topics: Healthcare
Retrieved: 28 July 2026
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ethics.ai (27 July 2026), “ESRVS: Extreme Semi-Supervised Retinal Vessel Segmentation with a Single Annotated Image,” evidence record 14047, https://ethics.ai/record/14047 (originally published by arXiv cs.AI).
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