Analysis of Graphically Interpreted RNFL Oct Data and Perimetry Data for Glaucoma Diagnosis and Progression using data Mining Approach

Abstract

People suffer from many eye diseases. Glaucoma is one of those diseases. It is second leading disease after cataract which leads to sudden vision loss in the patient. In India, glaucoma is the third leading cause for blindness. The vision loss due to glaucoma in a patient is so gradual that even the patient does not recognize the symptoms of this loss until there is a sudden loss in vision. Therefore, detection of glaucoma at early stage becomes very crucial. Numerous studies for the detection of glaucoma have been carried out by various researchers using image processing techniques as well as data mining techniques, but progression of glaucoma is not yet determined. newlineDiagnosis of glaucoma done in early phase helps to control the progression of vision loss. In this research, the researcher has developed Diagnosis of Glaucoma Progression (DGP) Framework, which helps in early detection as well as diagnosis of glaucoma and its progression. The framework is divided into three stages namely: newlinei. Calculation of CDR through image processing, newlineii. Find Correlation of Perimetry parameters and OCT parameters using Pearson Chi Square statistical method, newlineiii. Diagnosis of Glaucoma Progression through Decision Tree. newline newline