Automated Detection of Vascular Abnormalities in Diabetic Retinopathy using Morphological Entropic Thresholding with Preprocessing Median Fiter

Author(s):

G. Supraja , Bapatla Engineering College; M. Baby, Bapatla Engineering College

Keywords:

Vessel Segmentation, Image Processing, Diabetic Retinopathy, Preprocessing Median filter, Morphological filtering

Abstract:

Diabetic retinopathy is one of the serious eye diseases that can cause blindness and vision loss. The complication of the diabetes associated to retina of the eye is DR. A Patient with the disease has to undergo periodic screening of eye. For the diagnosis, ophthalmologists use color retinal images of a patient acquired from digital fundus camera. Ocular funds image can provide information on pathological changes caused by local ocular diseases and early signs of certain systemic diseases. The present study is aimed at developing an automatic system for the extraction of normal and abnormal features in color retinal images. The Preprocessing median fitter is applied before the Morphology. Morphological filter is tuned to match that part of vessel to be extracted in a green channel image. To classify the pixels into vessels and non-vessels local thresholding based on gray level co-occurrence matrix is applied. The performance of the method is evaluated on two publicly available retinal databases with hand labeled ground truths. The performance of retinal vessels on DRIVE database, sensitivity 91% accompanied by specificity of 94%. While for STARE database proposed method sensitivity 92% and specificity 90%. The system could assist the ophthalmologists, to detect the signs of diabetic retinopathy in the early stage, for a better treatment plan and to improve the vision related quality of life.

Other Details:

Manuscript Id	:	IJSTEV1I3023
Published in	:	Volume : 1, Issue : 3
Publication Date	:	01/10/2014
Page(s)	:	21-26

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