Fig. 3.

Schematic overview of the CNN model with two modules for tissue property mapping. The feature extraction module (FE) consists of four fully-connected layers (FNN), which is designed to mimic singular value decomposition to reduce the dimension of signal evolutions (McGivney et al., 2014). The U-Net structure was used for the spatially-constrained quantification (SQ) module to capture spatial information from neighboring pixels for improved quantification of tissue properties. MRF images of 3 contiguous slices (red) were used as input, and the corresponding reference T₁ and T₂ maps from the central slice were used as output for the network.