In this study, a deep model-based MR parameter mapping network termed as “DOPAMINE” was developed to reconstruct MR parameter maps from undersampled multi-channel k-space data. It consists of two models: 1) MR parameter mapping model which estimates initial parameter maps from undersampled k-space data with a deep convolutional neural network (CNN-based mapping), 2) parameter map reconstruction model which removes aliasing artifacts with a deep CNN (CNN-based reconstruction) and interleaved data consistency layer by embedded MR model-based optimization procedure.
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