Congress:
ECR25
Poster Number:
C-11988
Type:
Poster: EPOS Radiologist (scientific)
Authorblock:
R. Niemantsverdriet1, F. Hartmann1, M. P. A. Starmans1, M. Ronot2, R. L. Miclea3, V. Vilgrain2, M. Thomeer1, S. Klein1, LAI Consortium1; 1Rotterdam/NL, 2Paris/FR, 3Maastricht/NL
Disclosures:
Ruben Niemantsverdriet:
Nothing to disclose
Frederik Hartmann:
Nothing to disclose
Martijn Pieter Anton Starmans:
Nothing to disclose
Maxime Ronot:
Nothing to disclose
Razvan Lucian Miclea:
Nothing to disclose
Valérie Vilgrain:
Nothing to disclose
Maarten Thomeer:
Nothing to disclose
Stefan Klein:
Nothing to disclose
LAI Consortium:
Nothing to disclose
Keywords:
Liver, MR, Diagnostic procedure, Cancer
The LAI dataset will offer a valuable resource for developing and benchmarking AI algorithms aimed at automating the MRI-based diagnosis of solid-appearing liver lesions. The dataset and resulting algorithms hold the potential to enhance radiologists' decision-making and assist in patient referrals to specialised centres.