CapillaryX: A Fine-Tunable Pipeline for OCTA Segmentation and Feature Extraction

CapillaryX: A Fine-Tunable Pipeline for OCTA Segmentation and Feature Extraction | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article CapillaryX: A Fine-Tunable Pipeline for OCTA Segmentation and Feature Extraction Adham Elwakil, Thibaud Martin, José Vargas Quiros, Bart Liefers, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8176394/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Optical coherence tomography angiography (OCTA) enables non-invasive visualization of the retinal microvasculature, but widely used OCTA tools provide only global metrics such as vessel density or FAZ area, limiting their use for anatomically resolved phenotyping. We present CapillaryX, an open-source, end-to-end pipeline for anatomical segmentation and quantitative vascular feature extraction from superficial plexus OCTA projections. CapillaryX incorporates deep-learning models trained on the publicly annotated OCTA-500 dataset and fine-tuned using small annotated subsets to adapt across devices, fields of view, and slab definitions. The system segments arteries, veins, capillaries, and the foveal avascular zone (FAZ), and computes 34 vascular biomarkers, including bifurcation counts, vessel density, diameter and tortuosity distributions, small-vessel–specific metrics, and an extended set of FAZ morphometrics derived from contour, ellipse, convexity, and distance-based representations. Across OCTA-500, OphtalmoLaus, and Rotterdam Study datasets, CapillaryX achieved high agreement with expert annotations (artery–vein Dice > 85%, FAZ Dice > 92%) and maintained stable performance across heterogeneous acquisition settings. Extracted features showed consistent distributions across vendors and scan sizes, supporting their robustness for large-scale analyses. To our knowledge, CapillaryX is the first open-source tool to provide artery–vein–resolved and capillary-level OCTA biomarkers together with extended FAZ shape descriptors. By enabling anatomy-aware, standardized, and device-agnostic OCTA phenotyping, CapillaryX provides a foundation for reproducible imaging research in ophthalmology, neurology, and systemic vascular disease. Biomedical Engineering Nuclear Medicine & Medical Imaging Ophthalmology Artificial Intelligence and Machine Learning OCTA artery–vein segmentation vascular biomarkers FAZ morphology retinal imaging feature extraction medical image analysis Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8176394","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":548919029,"identity":"d96a95a0-4211-4afb-b323-2cb34331fee2","order_by":0,"name":"Adham Elwakil","email":"","orcid":"https://orcid.org/0009-0009-4881-6643","institution":"1 Platform for Research in Ocular Imaging, Fondation Asile des Aveugles, Jules Gonin Eye Hospital","correspondingAuthor":false,"prefix":"","firstName":"Adham","middleName":"","lastName":"Elwakil","suffix":""},{"id":548919030,"identity":"ee9c1814-0963-4f30-8dad-c2bf8579e91d","order_by":1,"name":"Thibaud 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