SuperMRF: deep robust reconstruction for highly accelerated magnetic resonance fingerprinting.

ABSTRACT:

Background

Magnetic resonance fingerprinting (MRF) is a rapid imaging technique for simultaneous mapping of multiple tissue properties such as T1 and T2 relaxation times. However, conventional pattern matching reconstruction and iterative low rank reconstruction methods may not take full advantage of the spatiotemporal content of MRF data and can require significant computational resources with long reconstruction times. Deep learning reconstruction using a three-dimensional (3D) convolutional neural network (CNN)-based method may enable high-quality, rapid MRF reconstruction. Evaluation of such proposed deep learning reconstruction methods for MRF is needed to clarify whether deep learning techniques adapted from other MR image reconstruction problems will yield benefits when empl

SUBMITTER: Li H 

PROVIDER: S-EPMC11994576 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature