Development of computer aided design system based on artificial neural network for macular hole detection - Jayapalan, Mohana Phriya (2021)
Medical imaging is a technique used to identify or study disease in the body. In order to obtain the retinal images, clinical ophthalmology broadly used a non-invasive medical imaging named optical coherence tomography (OCT). OCT images lead to visualize retina’s inner layers, which was important to identify the retinal diseases at the early stage. Macular Hole is one of the retinal disease that should be treated early. A Graphical User Interface (GUI) was created to detect the Macular Hole disease. In this paper, Computer Aided Design (CAD) system to detect Macular Hole eye disease has been developed. This disease diagnosed and need to be treated at beginning state as it will lead to vision lost if it get severe. An algorithm is proposed in this study which performs Macular Hole detection. There are browse image, pre-processing, segmentation, feature extraction and lastly classification steps. This study successfully classified the Macular Hole and normal retinal images correctly using Artificial Neural Network (ANN) classification. The accuracy of the net produced after several trials of retrain is 90%. The other statistical parameters such as precision, specificity and sensitivity was obtained from this project. In a conclusion, there was a way obtained from this study to diagnosis the patients who were suffer from this Macular Hole disease.