Segmentation of the aorta in systolic phase from 4D flow MRI: multi-atlas vs. deep learning.
Fiche publication
Date publication
février 2023
Journal
Magma (New York, N.Y.)
Auteurs
Membres identifiés du Cancéropôle Est :
Pr COCHET Alexandre
Tous les auteurs :
Marin-Castrillon DM, Geronzi L, Boucher A, Lin S, Morgant MC, Cochet A, Rochette M, Leclerc S, Ambarki K, Jin N, Aho LS, Lalande A, Bouchot O, Presles B
Lien Pubmed
Résumé
In the management of the aortic aneurysm, 4D flow magnetic resonance Imaging provides valuable information for the computation of new biomarkers using computational fluid dynamics (CFD). However, accurate segmentation of the aorta is required. Thus, our objective is to evaluate the performance of two automatic segmentation methods on the calculation of aortic wall pressure.
Mots clés
4D flow MRI, CFD, Deep learning segmentation, Multi-atlas segmentation
Référence
MAGMA. 2023 02 17;: