Novel Approach for Automatic Grading of Hyperemia in Four Different Classes as per IER using VGG16

Abstract

Hyperemia is a condition associated with conjunctiva of the eye. The work in this paper focuses on evaluating the redness of bulbar conjunctiva of human eye. The condition can be a result of numerous factors like injury to eye, friction due to dust particles, improper or prolonged use of contact lenses and it can also be an indication of serious condition like glaucoma. It is evident that if this condition is not given timely treatment then it can result into irreversible eye damage. Several methods have been proposed in past to grade hyperemia but due to human intervention involved the results were subjective in nature. This work proposes the use of pre trained convolutional neural network like VGG16 (named after Visual Geometry Group) to analyze and evaluate the degree of redness. The different classes of redness are in accordance with the Institute for Eye Research (IER) earlier referred as Cornea and Contact Lens Research Unit (CCLRU) grading scale which is universally accepted. The level of redness can further aid in specific line of treatment depending upon the ocular disease related if any. A hybrid model is proposed to automatize the entire process to achieve the desired objective.