MR Fingerprinting Reconstruction using Convolutional Neural Network (MRF-CNN)

The purpose of this study is to develop a MR fingerprinting (MRF) reconstruction algorithm using convolutional neural network (MRF-CNN). Better MRF reconstruction fidelity was achieved using our MRF-CNN compared with that of the conventional approach (R² of T₁: 0.98 vs 0.97, R² of T₂: 0.97 vs 0.59). This study further demonstrated the performance of our MRF-CNN, which was retrained using MR signal evolutions in the continuous parameter space with various levels of Gaussian noise, amidst noise contamination, suggesting that it may likely be a better alternative than the conventional MRF dictionary matching approach.