Fundus Image Segmentation Benchmark Dataset for Blood Vessel Segmentation

This benchmark dataset was created by combining three widely-used datasets: CHASEDB1, STARE, and DRIVE, to evaluate and enhance the performance of blood vessel segmentation models in fundus images. The dataset includes 28 high-resolution images from CHASEDB1, 20 diverse images from STARE, and 40 images from DRIVE, all preprocessed for uniformity in terms of size, contrast, and illumination. The data was split into training (70%), validation (15%), and testing (15%) sets, ensuring balanced representation for model development and unbiased evaluation. This comprehensive benchmark dataset has been openly published to aid in the development and comparison of models for robust fundus vessel segmentation.