Automated Segmentation of Retinal Vasculature
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Authors
Almi'ani, Muder M.
Barkana, Buket D.
Issue Date
2012
Type
Presentation
Language
Keywords
Faculty research day
Alternative Title
Abstract
Description
Image processing, analysis and computer vision techniques are increasing in all fields of medical science, and are especially applicable to modern ophthalmology. Automated image segmentation processing has the prospective for early detection of many diseases like the diabetes, by detecting changes in blood vessel in the retina images . The focus of this poster is on the automated segmentation of vessels in color images of the retina by describes the development of segmentation methodology in the processing of retinal blood vessel images using the region growing method and the Powerlaw transformation . The retina is the only location where blood vessels can be directly visualized non-invasively in vivo. Inspection of the retinal vasculature may reveal hypertension, diabetes, arteriosclerosis, cardiovascular disease, and stroke. In the same time with suitable feature extraction and automated classification methods, this segmentation method could form the basis of a quick and accurate test for the retina image, which would have many benefits for improved the access to screening people for risk or presence of diseases.
Citation
Poster 46