On the Spatial and Temporal Influence for the Reconstruction of Magnetic Resonance Fingerprinting

Balsiger, Fabian; Scheidegger, Oliver; Carlier, Pierre; Marty, Benjamin; Reyes, Mauricio (2019). On the Spatial and Temporal Influence for the Reconstruction of Magnetic Resonance Fingerprinting. Proceedings of machine learning research, pp. 27-38. JMLR

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Magnetic resonance fingerprinting (MRF) is a promising tool for fast and multiparametric quantitative MR imaging. A drawback of MRF, however, is that the reconstruction of the MR maps is computationally demanding and lacks scalability. Several works have been proposed to improve the reconstruction of MRF by deep learning methods. Unfortunately, such methods have never been evaluated on an extensive clinical data set, and there exists no consensus on whether a fingerprint-wise or spatiotemporal reconstruction is favorable. Therefore, we propose a convolutional neural network (CNN) that reconstructs MR maps from MRF-WF, a MRF sequence for neuromuscular diseases. We evaluated the CNN’s performance on a large and highly heterogeneous data set consisting of 95 patients with various neuromuscular diseases. We empirically show the benefit of using the information of neighboring fingerprints and visualize, via occlusion experiments, the importance of temporal frames for the reconstruction.

Item Type:

Journal Article (Original Article)


04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurology
04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic and Interventional Neuroradiology
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research

Graduate School:

Graduate School for Cellular and Biomedical Sciences (GCB)

UniBE Contributor:

Balsiger, Fabian, Scheidegger, Olivier


600 Technology > 610 Medicine & health
500 Science > 570 Life sciences; biology








Chantal Kottler

Date Deposited:

19 Dec 2019 13:59

Last Modified:

02 Mar 2023 23:32





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