A Case Study Approach: Iterative Prototyping Model Based Detection of Macular Edema in Retinal OCT Images

Abstract

Highly Reliable Automated medical diagnosis systems are of critical importance. Such systems aid in early detection of diseases and prevention of its further progression. Development of such a reliable and efficient software system is possible using a suitable system development life cycle (SDLC) model only. A SDLC model develops a system in a structured, deliberate and methodical mode and provides a very reliable and efficient system within limited resources and time. Macular edema is the blurring or loss of central vision which is caused as a result of Diabetic Retinopathy and Analysis of OCT images helps in identification of Macular Edema. The aim of this research is the successful detection of Macular Edema using Iterative Prototyping SDLC model. First the extraction of ILM layer has been done by using Active Contour based Segmentation and Curve Fitting Techniques then a new technique is proposed in this research for the successful localization of fovea in retinal ILM layer by using distance based method. Finally the detection of Macular edema has been done on the basis of analysis of fovea region. The system is evaluated using a local dataset of OCT images which is gathered with the help of Armed Forces institute of Ophthalmology. The dataset consists of 550 images and the developed system gives an accuracy of 84%. Keywords—SDLC, Iterative Prototyping, Fovea Centrails, Optical Coherence Tomography, Macula, Macular Edema.