Using AI to Diagnose Birth Defect in Fetal Ultrasound Images - Neuroscience News

Summary: Using datasets of fetal ultrasounds, a new AI algorithm is able to detect cystic hygroma, a rare embryonic developmental disorder, within the first trimester of pregnancy. In a new proof-of-concept study led by Dr. Mark Walker at the uOttawa Faculty of Medicine, researchers are pioneering the use of a unique AI-based deep learning model as an assistive tool for the rapid and accurate reading of ultrasound images. It's trailblazing work because although deep learning models have become increasingly popular in interpreting medical images and detecting disorders, figuring out how its application can work in obstetric ultrasonography is in its nascent stages. Few AI-enabled studies have been published in this field. The goal of the team's study was to demonstrate the potential for deep-learning architecture to support early and reliable identification of cystic hygroma from first trimester ultrasound scans.