The Blood Vasculature of the Retina Using Routine Segmentation

Abstract

ABSTRACTBiomedical imaging has helped the medical practitioners to facilitate treatments faster and more accurate than conventional methods. Automated technologies suffice the default preprocessing and identification from the images of the retina and their vessel vascular network. Human retinal diseases, leading to blindness, will be identified by the segmentation of blood vessels to enhance the statistical accuracy of intra-retinal layer thickness. This proposal overcomes the drawbacks of traditional angiogram techniques by coloring the retinal paths by fluorescent dyes. From the obtained results, automated segmentation by using the proposed technique has improved then compared methodologies. Employing Gabor filters in the preprocessing functions, elimination of false positives is greatly achieved with some modifications. The followed processes divide the retinal images into linear and curvature segments after implying Gabor constraints to obtain a predicted trajectory of vessels. Limiting the major chances of false positives and better vessel construction in this automated proposal are proved and discussed.