Flowdef: A MATLAB Application for Artifact-Reduced Choriocapillaris Flow-Void Quantification

Purpose: To introduce and validate Flowdef, an open–source MATLAB application that automatically excludes drusen– and vessel–related projection artifacts and enables region–specific quantification of choriocapillaris (CC) flow voids in eyes with age–related macular degeneration (AMD). Methods: Thirty eyes (10 healthy controls, 10 intermediate AMD, 10 dry AMD with geographic atrophy [GA]) underwent 6 × 6 mm OCT–angiography. Flowdef generates exclusion masks for drusen (Otsu threshold × 1.2) and superficial vessels (CLAHE + morphology) and identifies CC flow voids using a mean − 1 SD threshold. For GA eyes, an interactive affine registration aligns infrared and OCT en face images to delineate healthy, transition, and atrophic zones. Repeatability (same–day test–retest) and inter–rater reproducibility were assessed with intraclass correlation coefficients (ICC) and coefficients of variation (CV). Results: Flowdef processed all 30 eyes without failure. After artifact exclusion, atrophic zones showed the largest mean flow void area (1078 μm ² ) while healthy zones exhibited more numerous but smaller voids (mean area 871 μm ² ). Test–retest repeatability was excellent in GA (ICC 0.92−0.99) and control eyes (ICC 0.95−0.99) and variable in intermediate AMD (ICC 0.08−0.80). Inter–rater CV was <10% for most parameters except mean area in intermediate AMD (CV ≈ 200%). Conclusions: Flowdef provides a robust, freely available solution for artifact‑ reduced CC flow–void analysis and region‑ specific GA assessment, addressing key limitations of existing methods. Translational Relevance: By delivering reliable CC metrics with minimal user input, Flowdef can support longitudinal AMD monitoring and accelerate clinical research on emerging therapies.