Automated detection of early-stage ROP using a deep convolutional neural network - Docwire News

BACKGROUND/AIM: To automatically detect and classify the early stages of retinopathy of prematurity (ROP) using a deep convolutional neural network (CNN). METHODS: This retrospective cross-sectional study was conducted in a referral medical centre in Taiwan. Only premature infants with no ROP, stage 1 ROP or stage 2 ROP were enrolled. Overall, 11 372 retinal fundus images were compiled and split into 10 235 images (90%) for training, 1137 (10%) for validation and 244 for testing. A deep CNN was implemented to classify images according to the ROP stage.