We proposed a new sampling strategy for efficiently accelerating multiple acquisition MRI. The new sampling strategy is to obtain data along different phase encoding directions across multiple acquisitions. The proposed sampling strategy was evaluated in multi-contrast MR imaging (T1, T2, proton density) and multiple phase cycled (PC) balanced steady-state free precession (bSSFP) imaging by using compressed sensing (CS) algorithms and convolutional neural networks (CNNs) with central and/or random sampling pattern. Sampling along different phase encoding directions across multiple acquisitions was advantageous for accelerating multi-acquisition MRI, irrespective of reconstruction method, sampling pattern or datasets, with further improvement through transfer learning.
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