Jose D Vargas Quiros, Michael J Beyeler, Sofía Ortín-Vela, Sven Bergmann, Caroline C W Klaver, Bart Liefers
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引用次数: 0
Abstract
Purpose: Automatic extraction of retinal vascular biomarkers from color fundus images (CFIs) is crucial for large-scale studies of the retinal vasculature. We present VascX, an open-source software toolbox that extracts biomarkers from CFI artery-vein segmentations.
Methods: From a color fundus image, VascX computes artery and vein segmentation masks, extracts their centerlines, builds undirected and directed vessel graphs, and resolves vessel segments into longer vessels. A comprehensive set of biomarkers is derived, including vascular density, central retinal equivalents (CREs), and tortuosity. Spatially localized biomarkers may be calculated over grids placed relative to the fovea and optic disc.
Results: Our test-retest reproducibility analysis on repeat imaging of the same eye by different devices shows that most VascX biomarkers have moderate to excellent agreement (intraclass correlation coefficient > 0.5), with important differences in the level of robustness of different biomarkers. Our analyses of biomarker sensitivity to image perturbations and heuristic parameter values support these differences and further characterize VascX biomarkers.
Conclusions: VascX provides an explainable and flexible biomarker extraction toolbox that complements segmentation to produce reliable retinal vascular biomarkers. Our graph-based biomarker computation stages support reproducible, region-aware measurements suited for large-scale clinical and epidemiological research.
Translational relevance: VascX supports oculomics research by enabling easy extraction of existing biomarkers and rapid experimentation with new biomarkers. Its robustness and computational efficiency facilitate scalable deployment in large databases. VascX is released via GitHub and PyPI with comprehensive documentation and examples to facilitate adoption by ophthalmic researchers and clinicians.
期刊介绍：
Translational Vision Science & Technology (TVST), an official journal of the Association for Research in Vision and Ophthalmology (ARVO), an international organization whose purpose is to advance research worldwide into understanding the visual system and preventing, treating and curing its disorders, is an online, open access, peer-reviewed journal emphasizing multidisciplinary research that bridges the gap between basic research and clinical care. A highly qualified and diverse group of Associate Editors and Editorial Board Members is led by Editor-in-Chief Marco Zarbin, MD, PhD, FARVO.
The journal covers a broad spectrum of work, including but not limited to:
Applications of stem cell technology for regenerative medicine,
Development of new animal models of human diseases,
Tissue bioengineering,
Chemical engineering to improve virus-based gene delivery,
Nanotechnology for drug delivery,
Design and synthesis of artificial extracellular matrices,
Development of a true microsurgical operating environment,
Refining data analysis algorithms to improve in vivo imaging technology,
Results of Phase 1 clinical trials,
Reverse translational ("bedside to bench") research.
TVST seeks manuscripts from scientists and clinicians with diverse backgrounds ranging from basic chemistry to ophthalmic surgery that will advance or change the way we understand and/or treat vision-threatening diseases. TVST encourages the use of color, multimedia, hyperlinks, program code and other digital enhancements.
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