Digital image analysis of ultrasound images using machine learning to diagnose pediatric nonalcoholic fatty liver disease

Prevalence of nonalcoholic fatty liver disease (NAFLD) in children is rising with the epidemic of childhood obesity. Our objective was to perform digital image analysis (DIA) of ultrasound (US) images of the liver to develop a machine learning (ML) based classification model capable of differentiating NAFLD from healthy liver tissue and compare its performance with pixel intensity-based indices.

Source: Clinical Imaging - February 23, 2021 Category: Radiology Authors: Amit Das, Mary Connell, Shailesh Khetarpal Tags: Pediatric Radiology Source Type: research