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Reseach Article

Diabetic Retinopathycal Identification, Analysis and Diagnosis using Color Images

by Vinitha K., M. Sundaresan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 146 - Number 14
Year of Publication: 2016
Authors: Vinitha K., M. Sundaresan
10.5120/ijca2016910957

Vinitha K., M. Sundaresan . Diabetic Retinopathycal Identification, Analysis and Diagnosis using Color Images. International Journal of Computer Applications. 146, 14 ( Jul 2016), 46-50. DOI=10.5120/ijca2016910957

@article{ 10.5120/ijca2016910957,
author = { Vinitha K., M. Sundaresan },
title = { Diabetic Retinopathycal Identification, Analysis and Diagnosis using Color Images },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2016 },
volume = { 146 },
number = { 14 },
month = { Jul },
year = { 2016 },
issn = { 0975-8887 },
pages = { 46-50 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume146/number14/25470-2016910957/ },
doi = { 10.5120/ijca2016910957 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:50:30.525025+05:30
%A Vinitha K.
%A M. Sundaresan
%T Diabetic Retinopathycal Identification, Analysis and Diagnosis using Color Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 146
%N 14
%P 46-50
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image processing is deals with wave processing which the input data is a picture, and the result can be either an image or a set of parameters corresponding to the image. Medical Imaging is a wide technology which helps the doctors to see the interior portions of the body parts for easy diagnosis. The proposed system edge-based segmentation is applied for vessel extraction. It produces edge maps which are based on Kirsch edge detection methods. The proposed method discovers the eye disorder such as cardio vascular diseases and diabetic retinopathy. In order to evaluate the performance of proposed work, there are several statistical criteria which are related to the sensitivity, specificity, accuracy and precision.

References
  1. Rafael C Gonzalez and Richard E Woods (2013), “Digital Image Processing”, ISBN 978-81-317-2695-2, Pearson education, pp. 1-24 and 36-37.
  2. Mohd.imran khan, heena sheikh, Anwar mohd.mansuri, pradhumn soni, “a review of retinal vessel segmentation techniques and algorithms”, international journal of computer technology and application, volume 2(5), september-october 2011, pp. 1.
  3. Qiangfeng peter Lau, mong li lee, wynne hsu*, and Tien yin Wong, “simultaneously identifying all true vessels from segmented retinal images”, IEEE Transactions on biomedical engineering, 2013, pp. 1-6.
  4. Behdad Dashtbozorg, Ana Maria Mendonça, “an automatic graph-based approach for artery/vein classification in retinal images”, IEEE transactions on image processing, volume 23, no.3, March 2014, pp. 1-10.
  5. G.Mirsharif, F.Tajeripour, Sobhanmanesh, H.Pourreza, T.Banaee, “developing an automatic method for separation of arteries from veins in retinal images”, international conference on computer and knowledge engineering (ICCKE), october13-14, 2011, pp.1-15.
Index Terms

Computer Science
Information Sciences

Keywords

Biomedical Image Processing Retinal Structure vessel segmentation diabetic retinopathy Kirsch-Template Retinal Disease Diagnosis.