Fig. 1
From: A review on deep learning MRI reconstruction without fully sampled k-space
Flowchart of deep learning for MRI reconstruction with fully sampled data (a) and without fully sampled data (b). The difference between (a) and (b) is that (a) can train the network in a supervised manner. The network takes undersampled data and other prior as inputs and update parameters by backpropagation algorithms such as SGD and its variation. In reconstructing phase, the trained network can reconstruct high-quality images from the input