Assessment of LI-RADS efficacy in classification of hepatocellular carcinoma and benign liver nodules using DCE-MRI features and machine learning

Assessment of LI-RADS efficacy in classification of hepatocellular carcinoma and benign liver nodules using DCE-MRI features and machine learning

Purpose: The current study aimed to evaluate the efficiency of dynamic contrast-enhanced (DCE) MRI visual features in classifying benign liver nodules and hepatocellular carcinoma (HCC) using a machine learning model. Methods: 115 LI-RADS3, 137 LI-RADS4, and 140 LI-RADS5 nodules were included (392 n...

Full description

Bibliographic Details
Main Authors: Maryam Fotouhi, Fardin Samadi Khoshe Mehr, Sina Delazar, Ramin Shahidi, Babak Setayeshpour, Mohssen Nassiri Toosi, Arvin Arian
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:European Journal of Radiology Open
Subjects:
LI-RADS
Machine learning
Hepatocellular carcinoma
Dynamic contrast-enhanced MRI
Cirrhotic nodule
Online Access:http://www.sciencedirect.com/science/article/pii/S2352047723000618

Internet

http://www.sciencedirect.com/science/article/pii/S2352047723000618

Similar Items