1. Automatic Detection of Eye Cataract using Deep Convolution Neural Networks (DCNNs)
- Author
-
Mohammed Moshiul Hoque, Sadia Afroze, Nazmul Siddique, and Md. Rajib Hossain
- Subjects
genetic structures ,Artificial neural network ,Blindness ,Computer science ,business.industry ,Image processing ,Fundus (eye) ,medicine.disease ,Convolutional neural network ,eye diseases ,Convolution ,medicine ,Computer vision ,sense organs ,Artificial intelligence ,business - Abstract
Eye cataract is a condition in which the lens of the eye becomes clouding or less transparent. This affects the clear vision and is the most prevailing causes of blindness. Therefore, early cataract detection and prevention may reduce the blindness rate and surgery pain of the patients. This paper presents an eye cataract detection system using Deep Convolution Neural Network (DCNNs) comprising two modules: training and testing. The proposed DCNNs architecture is trained, validated and tested with retinal fundus images. Experimental result shows that the proposed system is capable of detecting eye cataract with high accuracy.
- Published
- 2020