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<p>We present the <i>SEoul Retinal Vessel Assessment Library</i> (<i>SERVAL</i>), a novel software platform for precise quantitative measurement of vascular structures in fundus images. <i>SERVAL</i> integrates deep learning-based automatic artery and vein mask initialization, subpixel vessel centerline and boundary refinement, and interactive editing tools within a user-friendly graphical interface. From the refined artery and vein delineations, it enables accurate computation of a wide range of vessel assessment metrics, facilitating better characterization of complex vascular structures. We evaluate <i>SERVAL</i> through: (1) comparative analyses with existing platforms, highlighting its superior precision and structural detail; (2) longitudinal image studies demonstrating measurement consistency; and (3) a usability study confirming its clinical practicality. We expect <i>SERVAL</i> to serve as a valuable tool in clinical research, supporting the development of novel vascular biomarkers and diagnostic metrics for retinal and systemic diseases.</p>

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Improving retinal vessel assessment precision by integrating deep learning with interactive editing and graphical modeling

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月24日

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  • Sojung Go,
  • Jaemin Chae,
  • Uichan Kim,
  • Jongsoo Lim,
  • Jooyoung Kim,
  • Stephen Hogg,
  • Emanuele Trucco,
  • Sang Jun Park,
  • Soochahn Lee

摘要

We present the SEoul Retinal Vessel Assessment Library (SERVAL), a novel software platform for precise quantitative measurement of vascular structures in fundus images. SERVAL integrates deep learning-based automatic artery and vein mask initialization, subpixel vessel centerline and boundary refinement, and interactive editing tools within a user-friendly graphical interface. From the refined artery and vein delineations, it enables accurate computation of a wide range of vessel assessment metrics, facilitating better characterization of complex vascular structures. We evaluate SERVAL through: (1) comparative analyses with existing platforms, highlighting its superior precision and structural detail; (2) longitudinal image studies demonstrating measurement consistency; and (3) a usability study confirming its clinical practicality. We expect SERVAL to serve as a valuable tool in clinical research, supporting the development of novel vascular biomarkers and diagnostic metrics for retinal and systemic diseases.