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Multi-parametric quantitative magnetic resonance imaging (mqMRI) has important applications in clinic. Multiple overlapping-echo detachment (MOLED) imaging can achieve single-shot mqMRI. However, the existing methods mainly focus on single-slice reconstruction. To improve the reconstruction quality of parametric maps by exploring data redundancy among adjacent slices, we proposed a multi-slice information sharing method via multiple modulation patterns of MOLED k-space and deep neural network. The results show that our method can effectively utilize the correlation information among adjacent slices and improve the reconstruction quality compared to the single-slice reconstruction method.
Dai et al. (Wed,) studied this question.