5 papers
retinalysis-vascx: An explainable software toolbox for the extraction of retinal vascular biomarkers
Jose D. Vargas Quiros, Michael J. Beyeler, Sofia Ortin Vela +5
Automatic extraction of retinal vascular biomarkers from color fundus images (CFI) is crucial for large-scale studies of the retinal vasculature. We present VascX, an open-source P…
Rotterdam artery-vein segmentation (RAV) dataset
Jose Vargas Quiros, Bart Liefers, Karin van Garderen +3
Purpose: To provide a diverse, high-quality dataset of color fundus images (CFIs) with detailed artery-vein (A/V) segmentation annotations, supporting the development and evaluatio…
retinalysis-fundusprep: A python package for robust color fundus image bounds extraction
Jose Vargas Quiros, Bart Liefers, Karin van Garderen +2
Color fundus image (CFI) bounds detection and contrast enhancement are fundamental tasks in automatic CFI analysis. We present an open-source algorithm, published as a Python packa…
Uncertainty-aware retinal layer segmentation in OCT through probabilistic signed distance functions
Mohammad Mohaiminul Islam, Coen de Vente, Bart Liefers +3
In this paper, we present a new approach for uncertainty-aware retinal layer segmentation in Optical Coherence Tomography (OCT) scans using probabilistic signed distance functions…
VascX Models: Model Ensembles for Retinal Vascular Analysis from Color Fundus Images
Jose Vargas Quiros, Bart Liefers, Karin van Garderen +4
We introduce VascX models, a comprehensive set of model ensembles for analyzing retinal vasculature from color fundus images (CFIs). Annotated CFIs were aggregated from public data…