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PROJECT TITLE :

Segmentation of Blood Vessels and Optic Disc in Retinal Images - 2014

ABSTRACT:

Retinal image analysis is increasingly prominent as a nonintrusive diagnosis method in fashionable ophthalmology. In this paper, we have a tendency to present a completely unique method to segment blood vessels and optic disk in the fundus retinal pictures. The method may be used to support nonintrusive diagnosis in fashionable ophthalmology since the morphology of the blood vessel and also the optic disk is a vital indicator for diseases like diabetic retinopathy, glaucoma, and hypertension. Our method takes as first step the extraction of the retina vascular tree using the graph cut technique. The blood vessel data is then used to estimate the situation of the optic disk. The optic disk segmentation is performed using 2 various ways. The Markov random field (MRF) image reconstruction methodology segments the optic disk by removing vessels from the optic disk region, and therefore the compensation issue technique segments the optic disk using the previous native intensity information of the vessels. The proposed methodology is tested on 3 public datasets, DIARETDB1, DRIVE, and STARE. The results and comparison with different methods show that our method achieved exceptional performance in segmenting the blood vessel and optic disk.


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Markov Processes Diseases Feature Extraction Random Processes Image Segmentation Medical Image Processing Biomedical Optical Imaging Blood Vessels Eye Vessel Segmentation Graph Cut Segmentation Optic Disk Segmentation Retinal Images
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