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To develop and evaluate an integrated motion correction and dictionary learning (MoDic) technique to accelerate data acquisition for myocardial T₁ mapping with improved accuracy.

MoDic integrates motion correction with dictionary learning–based reconstruction. A random undersampling scheme was implemented for slice‐interleaved T₁ mapping sequence to allow prospective undersampled data acquisition. Phantom experiments were performed to evaluate the effect of reconstruction on T₁ measurement. In vivo T₁ mappings were acquired in 8 healthy subjects using 6 different acceleration approaches: uniform or randomly undersampled k‐space data with reduction factors (R) of 2, 3, and 4. Uniform undersampled data were reconstructed with SENSE, and randomly undersampled k‐space data were reconstructed using dictionary learning, compressed sensing SENSE, and MoDic …