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Abstract #1356

Accelerated Magnetic Resonance Fingerprinting Reconstruction using Majorization-Minimization

Yang Li1, SHUAI Wang1, Edward S. Hui2,3, Di Cui2, Hing-Chiu Chang2, and Yik-Chung Wu1

1Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong, 2Department of Diagnostic Radiology, The University of Hong Kong, Pokfulam, Hong Kong, 3The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Pokfulam, Hong Kong

Magnetic resonance fingerprinting (MRF) is a novel and efficient method for the estimation of MR parameters, such as off-resonance (DB­0), proton density (PD), T1 and T2. Because of the highly undersampled readout that is conventionally used, large number of dynamics (e.g. <1000) are often acquired for maintaining the fidelity of MR parameter estimations (a.k.a. dictionary matching). In this study, we propose a new algorithm, MRF reconstruction using majorization-minimization (mmMRF), such that fidelity of dictionary matching can remain similar even when significantly less number of dynamics are available.

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