Detection of retinal hemorrhage in fundus images using ANFIS classification and FCM with cuckoo search optimization algorithm

In the fundus image screening framework, reliable detection of retinal hemorrhage is required. Retinal hemorrhages are created by diabetic retinopathy and hypertension. In our study propose to build up the retinal discharge fundus images by the method for pre-processing, feature extraction, classification, and segmentation by different strategies and methodologies. By utilizing ANFIS the affected and non-affected images are accurately divided and the affected images are segmented by FCM-CS optimization methods. From that, the accuracy, specificity, sensitivity, FAR and FRR are broke down for that segmented images. The outcomes demonstrate that the proposed system achieves the greatest accuracy and performs optimal value contrasted with existing methodologies.