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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