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New pipeline estimates retinal vascular health with high accuracy

Researchers have developed a five-stage pipeline for estimating the arteriolar-to-venular ratio (AVR) from retinal fundus images, a marker of vascular health. This system provides inspectable intermediate outputs at each stage, allowing for transparent error tracing. Initial testing on a small cohort of 30 images showed high accuracy (96.7%) and an F1-score of 0.968, though further validation on larger, clinically graded cohorts is necessary. AI

IMPACT This research offers a more transparent approach to medical image analysis, potentially improving diagnostic accuracy and trust in AI systems for healthcare.

RANK_REASON This is a research paper detailing a new methodology for medical image analysis. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New pipeline estimates retinal vascular health with high accuracy

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This is a research paper detailing a new methodology for medical image analysis. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Sharan Sharmeela Karuppannan, Yoga Sri Varshan V, Subin Sahayam, Umarani Jayaraman ·

    A Stage-Wise Explainable Pipeline for Arteriolar-to-Venular Ratio Estimation and Retinopathy Screening

    arXiv:2611.14013v1 Announce Type: cross Abstract: The arteriolar-to-venular diameter ratio (AVR) is a clinically motivated marker of retinal vascular health. We present a five-stage pipeline for AVR estimation and exploratory retinopathy screening from fundus images, with inspect…