{
  "id": 577,
  "url": "https://arxiv.org/abs/2606.26712v1",
  "title": "MLFFM-SegDiff: A Multi-Level Feature Fusion Diffusion Model for Skin Lesion Segmentation",
  "summary": "Skin lesion segmentation is a key task in computer-aided dermatological diagnosis, where accuracy directly impacts downstream analysis and disease classification. However, dermoscopic images are challenging due to blurred boundaries, low contrast, large shape variations, and artifacts such as hair and shadows. Recently, diffusion models have shown strong performance in medical image segmentation thanks to their progressive denoising and distribution modeling capabilities. Nevertheless, existing ",
  "authors": "Jingjun Gu, Chaojie Shen, Yifeng Cao, Wei Zhang, Yiliu Li, Aobo Fan",
  "category": "research",
  "topics": "healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2026-06-25T07:45:28.000Z",
  "fetched_at": "2026-07-14T14:14:37.249Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/577",
  "original_url": "https://arxiv.org/abs/2606.26712v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}