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

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.