Diabetic Retinopathy Analysis using Retinal Image Matching  
  Authors : Asha Mundhe; Dr. M.S. Nagmode

 

In development of automated screening systems for diabetic retinopathy, main step is Optic disc detection and vascular feature extraction. Here, we propose a method for diagnosis of Diabetic Retinopathy using optic disc and vascular features based retinal image matching. This method can be used for Person identification using retinal images or automatic detection of Diabetic Retinopathy. Optic disc and vascular features are the two important features extracted from the retinal image. On the basis of these features, corresponding images are matched. Image matching method identifies the same blood vessel in the corresponding images and compare the desired features. Initial results are good and demonstrate that the proposed method is suitable for Diagnosis of Diabetic Retinopathy.

 

Published In : IJCAT Journal Volume 1, Issue 7

Date of Publication : 31 August 2014

Pages : 371 - 377

Figures :21

Tables : --

Publication Link : Diabetic Retinopathy Analysis using Retinal Image Matching

 

 

 

Asha Mundhe : Department of E&TC Engineering, University of Pune, MIT College of Engineering, Pune, Maharashtra, India

Dr. M.S. Nagmode : Department of E&TC Engineering, University of Pune, MIT College of Engineering, Pune, Maharashtra, India

 

 

 

 

 

 

 

Diabetic Retinopathy

Retinal Image

Optic Disc

Vessel Bifurcation

Branch and Crossover Points

Retinal Image Matching

This paper presents feature based retinal image matching. The method is highly suitable for diabetic retinopathy analysis. It is efficient in matching the retinal images and searching the corresponding vascular features set. Applying the method, the medical practitioners can examine significantly changes on different vascular features for each of the vesselsegments in retinal fundus images. For biometric security application, this method requires simple modification. We are in process of gathering multiple images forthe same person to have a large scale analysis and next validation of the method.

 

 

 

 

 

 

 

 

 

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