Feasibility of virtual T2-weighted fat-saturated breast MRI images by convolutional neural networks

Feasibility of virtual T2-weighted fat-saturated breast MRI images by convolutional neural networks

Abstract Background Breast magnetic resonance imaging (MRI) protocols often include T2-weighted fat-saturated (T2w-FS) sequences, which support tissue characterization but significantly increase scan time. This study aims to evaluate whether a 2D-U-Net neural network can generate virtual T2w-FS (Vir...

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Bibliographic Details
Main Authors: Andrzej Liebert, Dominique Hadler, Chris Ehring, Hannes Schreiter, Luise Brock, Lorenz A. Kapsner, Jessica Eberle, Ramona Erber, Julius Emons, Frederik B. Laun, Michael Uder, Evelyn Wenkel, Sabine Ohlmeyer, Sebastian Bickelhaupt
Format: Article
Language:English
Published: SpringerOpen 2025-05-01
Series:European Radiology Experimental
Subjects:
Artificial intelligence
Breast neoplasms
Diagnostic imaging
Magnetic resonance imaging
Neural network (computer)
Online Access:https://doi.org/10.1186/s41747-025-00580-3
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