Figure 1.

An overview of the MTC-MRF quantification scheme with B₀ and B₁ correction. (A) In the training phase, MR fingerprints are simulated using two-pool Bloch equations with randomly selected tissue and nominal scan parameters (${\text{p}}_{\text{scan}}^{\text{nom}}$) within the pre-defined ranges. The simulated fingerprints and the corresponding scan parameters are fed to the recurrent neural network to estimate the tissue parameters. (B) In the test phase, the corrected scan parameters (${\text{p}}_{\text{scan}}^{\text{corr}}$) are calibrated using the acquired ΔB₀ and relative B₁ (rB₁) values, and fed to the trained RNN model.