You Only Look Once (YOLO) with Convolution Neural Network (CNN) Classification for Preterm Baby’s Retinopathy Images

Retinopathy of Preterm (ROP) is becoming more common in babies as the number of preterm individuals grows dramatically around the world. ROP can be effectively treated, but it requires constant screening and early diagnosis. Implementing a computer-aided approach based on image processing is among the simplest ways to diagnose ROP. Deep learning approaches have shown to be quite effective in medical image analysis in this regard. For Noise removal Laplacian of Gaussian (LoG) filter is used. In comparison to Random Forest (RF), Artificial Neural Network (ANN) and Convolutional Neural Network (CNN), the method proposed in this research aims to detect the ROP by using YOLO algorithm to accurately detect and classify retinal fundus images according to its severity. Dataset is collected from Kaggle and the Python package. The experimental studies show that the suggested work is stable, trustworthy, and yields promising ROP detection results with accuracy of 94.63%, sensitivity of 0.94, specificity of 0.80 and F-Measure of 0.8 respectively. The tool used for execution is python.