Identification of Retinoblastoma Using Backpropagation Neural Network

Abstract

Retinoblastoma (eye cancer) is an eye disease that is usually suffered by children that attack the thin nerve tissue behind the eyes (the part which is sensitive to light). Retinoblastoma can attack one or both eyes and it is a type of disease that can be caused by a genetic mutation called Retinoblastoma1 (RB1). On manual physical examination using ophthalmoscopy by a doctor or an expert there is a yellowish white / white cancer on the fundus that is often caused by the vascularization. That is why it needs a method that can be done to identify retinoblastoma disease through retinal fundus images automatically. In this research the method used is Backpropagation Neural Network using input of retinal fundus image. The stages which is done to identify retinoblastoma disease are image processing (resize, grey scaling, morphological close operation, and optic disk elimination), feature extraction using Grey Level Co-occurrence Matrix method and then classification using backpropagation neural network. After testing on the system in this research, it was concluded that the method used is able to identify retinoblastoma disease with accuracy 90%.