Diabetic Retinopathy Prediction using Modified Inception V3 Model Structure

Authors

  • Shwetha G. K. NMAM Institute of Technology , Affiliated to NITTE (Deemed to be University) , India
  • Udaya Kumar Reddy K. R. School of Engineering, Dayananda Sagar University , Bengaluru, India Alva’s Institute of Engineering & Technology , Moodubidire , India
  • Jayantkumar A. Rathod School of Electronics and Communication Engineering,REVA University,Bengaluru,India
  • Sathyaprakash B. P. Alva’s Institute of Engineering & Technology , Moodubidire , India
  • Lolakshi P. K. Alva’s Institute of Engineering & Technology , Moodubidire , India

Keywords:

Diabetic Retinopathy (DR), Retinal Fundus Images, Histogram Equalization, Contrast Enhancement, Optic disc, Morphological Techniques

Abstract

The analysis of clinical findings revealed that more than 10% of diabetic individuals have an elevated risk of eye issues. Diabetic Retinopathy (DR) is a type of eye illness that impacts 80-85% of persons suffering for more than 10 years from diabetes. In hospitals, retinal fundus images are commonly employed for the identification and study of diabetic retinopathy. The unprocessed retinal fundus images are difficult for machine learning approaches to analyze. Original retinal fundus images are pre-processed utilizing green channel separation, histogram equalization, contrast enhancement, and scaling procedures. For statistical analysis, 14 attributes are additionally collected from preprocessed images. Technique for the detection of retinal lesions can aid in the earlier identification and treatment of a frequently found condition, diabetic retinopathy. We introduce a new criterion for the identification of the optic disc in which we initially identify the significant blood vessels and then utilize their intersection to estimate the position of the optic disc. Future localized utilizing color characteristics. We also demonstrate that a set of attributes, including blood vessels, mucus, micro aneurysms, and hemorrhages, may be recognized with high precision utilizing different morphological techniques applied suitably.

 

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VGG 16 Structure

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Published

16.01.2023

How to Cite

G. K., S. ., Reddy K. R., U. K. ., A. Rathod, J. ., B. P., S. ., & P. K., L. . (2023). Diabetic Retinopathy Prediction using Modified Inception V3 Model Structure. International Journal of Intelligent Systems and Applications in Engineering, 11(1), 261–268. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2466

Issue

Vol. 11 No. 1 (2023)

Section

Research Article

License

Copyright (c) 2023 Shwetha G. K., Udaya Kumar Reddy K. R., Jayantkumar A. Rathod, Sathyaprakash B. P., Lolakshi P. K.

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