Khursheed Aurangzeb*, Syed Irtaza Haider, Musaed Alhussein
CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1381-1405, 2024, DOI:10.32604/cmc.2024.048987
Abstract In this work, we aim to introduce some modifications to the Anam-Net deep neural network (DNN) model for segmenting optic cup (OC) and optic disc (OD) in retinal fundus images to estimate the cup-to-disc ratio (CDR). The CDR is a reliable measure for the early diagnosis of Glaucoma. In this study, we developed a lightweight DNN model for OC and OD segmentation in retinal fundus images. Our DNN model is based on modifications to Anam-Net, incorporating an anamorphic depth embedding block. To reduce computational complexity, we employ a fixed filter size for all convolution layers… More >
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