Yoga Sri Varshan V
ABSTRACT
Retinal blood vessels are the arteries and veins that supply blood to the human eye. Fundus images obtained through a fundus camera capture retinal information like, the macula, optic disc, cup, fovea, retinal blood vessels, and abnormalities. The retinal blood vessels are miniature and are usually measured in micrometers. It is difficult and time-consuming to study retinal vessels from a fundus image. Generally, a detailed vessel study requires costly equipment like Ocular Coherence Tomography (OCT) and is comparatively less available at hospitals than a fundus camera. Blood vessels are connected throughout the body. Studying retinal blood vessel health can help ophthalmologists and doctors understand the overall health of blood vessels across the body non-invasively. Narrowing of blood vessels can make a person prone to many diseases, like hypertension, cardiovascular disease, and stroke. A few methods aim to automate the task using Computer Aided Diagnosis (CAD). The work proposes a novel and relatively less complex algorithm for calculating the diameter of a given retinal blood vessel at a given distance from the optic disc center in a fundus image. The approach aims to compute the artery-to-vein diameter ratio of retinal blood vessels at a given distance from the center of the optic disc. The proposed method has been tested on the LES-AV 2020 dataset and it achieved an approximate artery-to-vein diameter ratio (AVR) of 2:3, which is in line with the average healthy AVR in the literature. Therefore, the proposed method is accurate and can be extended to find AVR in various clinical scenarios to detect and study any abnormalities.
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Index Terms
- An Algorithm to Calculate Retinal Vessel Diameter in Fundus Images
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