Automated Detection of Retinal Detachment Using Deep Learning-Based Segmentation on Ocular Ultrasonography Images.

Purpose: This study aims to develop an automated pipeline to detect retinal detachment from B-scan ocular ultrasonography (USG) images by using deep learning-based segmentation.

Methods: A computational pipeline consisting of an encoder-decoder segmentation network and a machine learning classifier was developed, trained, and validated using 279 B-scan ocular USG images from 204 patients, including 66 retinal detachment (RD) images, 36 posterior vitreous detachment images, and 177 healthy control images. Performance metrics, including the precision, recall, and F-scores, were calculated for both segmentation and RD detection.