Open AccessA Novel Eye Cataract Diagnosis and Classification Using Deep Neural Network
Author(s) -
S. Jayachitra,
K. Nitheesh Kanna,
G Pavithra,
T. Ranjeetha
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1937/1/012053
Subject(s) - blindness , net (polyhedron) , cataract surgery , artificial intelligence , computer science , artificial neural network , optometry , medicine , sensitivity (control systems) , ophthalmology , mathematics , engineering , geometry , electronic engineering
Eye Cataract is one of the main causes of blindness. It affects mostly people at the age of 60.In India, half of the aged people have cataract or have already treated by a surgery. The cataract identification is highly complicated in an early stage. To achieve this, experts chose the concepts of Deep Learning. In this paper we proposed Dense-Net and U-Net to detect and classify the eye cataract. Further, we took 200 samples of eye image to determine the presence of cataract with its severity. Finally, the comparison of Dense-Net and U-Net are tabulated interms of accuracy, sensitivity, and specificity. Hence, it proven that U- Net gives 10% accurate results than Dense Net.