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. Author manuscript; available in PMC: 2019 Oct 4.
Published in final edited form as: IEEE Trans Med Imaging. 2019 Feb 13;38(10):2364–2374. doi: 10.1109/TMI.2019.2899328

Fig. 1.

Fig. 1.

Schematic overview of our proposed two-step deep learning model for spatially-constrained tissue quantification in MRF. FNN: fully-connected neural network. CNN: convolutional neural network. The number of channels (each with paired FNN and CNN) is equal to the number of tissue properties to be estimated (i.e., 2 in this study).