Classification of Diabetic Maculopathy from Retinal Images - Manjulasri, R.; Swetha, D.; SampurnaLakshmi, P. (International Journal of Engineering and Technology, 2018)
Diabetes mellitus is a significant cause forÂ Â visible loss and vision deficit. All patients with type 1Â diabetes and greater than 60% of type 2 diabetes suffer a few degrees of retinopathy, due to diabetes for a long time. The damage of the normal vision, contingent upon the significant of damage of the macula, is due to diabetes retinopathy, which extends to Maculopathy. The main objective ofÂ this work is to designÂ aÂ method and develop software to identify the seriousness ofÂ diabetic maculopathy, using image processing techniques on retinal images. The proposed framework classifies different types of maculopathy as Normal orÂ clinically important andÂ non-clinically significant maculopathy fromÂ fundus images. The features had been separated from the original fundus image with morphological operations and strengthened with two classifiers, the Artificial Neural method (ANN) and probabilistic neural methods (PNN). The proposed methodÂ established that ANN has the best characterization performance efficiency of 96.67%Â comparedÂ to PNN.Â Â Â