Lesions and Blood Vessel Detection in Eye Retinal Image
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 6
Abstract
Medical image analysis, applied to clinical diagnosis in ophthalmology is currently drawing intense interest of scientists and physicians. It enables the physician to measure important structures in an image, compare sequential images, aggregate images similar in content and finally obtain automated diagnosis from images. This involves many challenging steps like image processing, segmentation, classification, registration, recognition of objects from arbitrary viewpoints and inferencing. Information about blood vessels in the eye can be used in grading disease severity or as a part of automated diagnosis of disease with ocular manifestations. Systemic or local ocular diseases, causes some measurable abnormalities in diameter, colour and tortusity of the blood vessels in the retina. Disease like diabetes, as it progresses, generates new blood vessels (Neovascularization) in the retina causing loss of vision. This project work addresses issues in the development of automatic system for the analysis of retinal angiographic images, providing focus on the segmentation of the blood vessels and lesion detection. Kirsch Template Matching Algorithm is proposed for detecting the blood vessels in the retinal images and an effective approach to detect lesions in color retinal images. The proposed method uses two dimensional Kirsch Template Matching, which detect the blood vessel as the whole not only the edges and do the noise filtering in a single step and shows small vessels, capillaries to produce complete vessel map there by increasing the diagnostic ease of the ophthalmologist. The lesion detection algorithm, automatically take care of the non-uniform illumination using a power law transformation and classifies the lesion like regions in the retina image.
Authors and Affiliations
M. Rajab Rosa , Fathima, V. Premkumar, P. Sophia
Keywords
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