arXiv Artificial Intelligence

Hybrid Approach for Enhancing Lesion Segmentation in Fundus Images

1 hour ago 30.09.2026 07:00 👁 1 views
Hybrid Approach for Enhancing Lesion Segmentation in Fundus Images

Quick summary

arXiv:2509.25549v3 Announce Type: replace-cross Abstract: Choroidal nevi are common benign pigmented lesions in the eye, with a small risk of transforming into melanoma. Early detection is critical to improving survival rates, but misdiagnosis or delayed diagnosis can lead to poor outcomes. Despite advancements in AI-based image analysis, diagnosing choroidal nevi in colour fundus images remains challenging, particularly for clinicians without specialized expertise. Existing datasets often suffer from low resolution and inconsistent labelling, limiting the effectiveness of segmentation models.

Key takeaways

  • arXiv:2509.25549v3 Announce Type: replace-cross Abstract: Choroidal nevi are common benign pigmented lesions in the eye, with a small risk of transforming into melanoma.
  • Early detection is critical to improving survival rates, but misdiagnosis or delayed diagnosis can lead to poor outcomes.
  • Despite advancements in AI-based image analysis, diagnosing choroidal nevi in colour fundus images remains challenging, particularly for clinicians without specialized expertise.

Why it matters

The importance of “Hybrid Approach for Enhancing Lesion Segmentation in Fundus Images” will be measured by what changes in practice. User behavior, access conditions, verifiable performance and responsible-use outcomes are the signals worth following.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗