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Abstract #4269

Accelerated Magnetic Resonance Fingerprinting Using Convolutional Neural Network

Ying Liao1, Qiang Zhang1, Di Cui2, Edward Sai-Kam Hui2, and Huijun Chen1

1Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China, 2Department of Diagnostic Radiology, The University of Hong Kong, Pokfulam, Hong Kong

The purpose of this work is to accelerate the acquisition of Magnetic Resonance Fingerprinting (MRF) using Convolutional Neural Network (CNN). Compared with traditional MRF reconstruction using 1000 time points, our CNN model shows better reconstruction fidelity in T2 and similar reconstruction fidelity in T1 using 300 time points. Our study suggests that CNN-based method may be an effective tool in the acceleration of MRF reconstruction.

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