Retinal Image Processing Using Neural Networks For Disease Prediction

Authors(2) :-R. Venkatesan, E. Saranya

In medical field, diagnoses of diseases are competently carried out by using the image processing. Human eye is an important organ that reacts to light and has several purposes. The eye has a number of components but it is not limited to the cornea, iris, pupil, lens, retina, and macula, optic nerve, choroid and vitreous. Retinal images play vital role in several applications such as disease diagnose and human recognition. Retinal image analysis is particularly a complicated task because of the variability of the images in terms of the color, the morphology of the retinal anatomical pathological structure and the existence of particular features in different patients, which may lead to an erroneous interpretation. Image processing techniques were used for dark object detection to analyze the condition of the input image, to enhance the input image in order to make it suitable for processing of the retinal image, to improve visibility of Microaneyrysm in color fundus images. K-Nearest algorithm is used to detect the blood vessels effectively for segmentation process and Deep Neural algorithm is used to classify the diagnose the diseases such as stroke, heart attack and cardio vascular disease by segmenting optic disc and to predict retinal disease using Ellipse Fitting method. Experimental results show that good accuracy in disease prediction.

Authors and Affiliations

R. Venkatesan
PG Scholar & Computer Science and Engineering, Anna University/Sir Issac Newton college of Engineering and Technology, Nagapattinam, Tamilnadu, India
E. Saranya
Assistant Professor of Computer Science and Engineering, Anna University/Sir Issac Newton College of Engineering and Technology, Nagapattinam, Tamilnadu, India

Image Processing, Eye Components, Disease Diagnosis, Diabetic Prediction

  1. Abdallah,Mariem Ben,et al. "Automatic extraction of blood vessels in the retinal vascular tree using multiscale medialness." Journal of Biomedical Imaging 2015 (2015): 1.
  2. Kaur,Manvir,and Rajneesh Talwar. "Automatic Extraction of Blood Vessel and Eye Retinopathy Detection." European Journal of Advances in Engineering and Technology 2.4 (2015): 57-61.
  3. Wang,Shuangling,et al. "Hierarchical retinal blood vessel segmentation based on feature and ensemble learning." Neurocomputing 149 (2015): 708-717.
  4. Vidyashree,M. R.,M. V. Usha,and vtu ewit. "Locating the optic nerve and blood vessel in a retinal images using graph partition method." (2015).
  5. Annunziata,Roberto,et al. "Leveraging multiscale hessian-based enhancement with a novel exudate inpainting technique for retinal vessel segmentation." IEEE journal of biomedical and health informatics 20.4 (2016): 1129-1138.
  6. N. Srivastava,G. Hinton,A. Krizhevsky,I. Sutskever,and R. Salakhutdinov,"Dropout: A simple way to prevent neural networks from overfitting," The Journal of Machine Learning Research,vol. 15,no. 1,pp. 1929-1958,2014.
  7. Y. Bengio,P. Lamblin,D. Popovici,H. Larochelle et al.,"Greedy layer-wise training of deep networks," Advances in neural information processing systems,vol. 19,p. 153,2007.
  8. M. Fraz,P. Remagnino,A. Hoppe,B. Uyyanonvara,A. Rudnicka,C. Owen,and S. Barman,"Blood vessel segmentation methodologies in retinal images - a survey," Comput. Methods Prog. Biomed. vol. 108,no. 1,pp. 407-433,Oct. 2012.
  9. J. Staal,M. D. Abràmoff,M. Niemeijer,M. A. Viergever,and B. van Ginneken,"Ridge-based vessel segmentation in color images of the retina," Medical Imaging,IEEE Transactions on,vol. 23,no. 4,pp. 501-509,2004.
  10. A. Hoover, V. Kouznetsova, and M. Goldbaum, "Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response," Medical Imaging,IEEE Transactions on,vol. 19,no. 3,pp. 203-210,2000.

Publication Details

Published in : Volume 3 | Issue 2 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 202-209
Manuscript Number : CSEIT1831490
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

R. Venkatesan, E. Saranya, "Retinal Image Processing Using Neural Networks For Disease Prediction ", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 2, pp.202-209, January-February-2018.
Journal URL : http://ijsrcseit.com/CSEIT1831490

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