Magnetic resonance imaging reconstruction using machine learning for multi-contrast acquisitions

A non-transitory computer-readable storage medium having executable instructions stored thereon that, when executed by one or more processors of a magnetic resonance imaging (MRI) device, cause the MRI device to reconstruct a sequence of magnetic resonance imaging (MRI) images by:

• obtaining a sequence of MRI measurement datasets, MRI measurement datasets of the sequence of MRI measurement datasets each being acquired (i) using at least one undersampling trajectory in k-space and a receiver coil array, and (ii) at multiple time offsets with respect to at least one excitation pulse and/or at least one refocusing pulse;
• and
• performing, based on the MRI measurement datasets, an iterative process to obtain a sequence of reconstructed MRI images,
• wherein the iterative process comprises, for each iteration of multiple iterations, a regularization operation and a data-consistency operation to obtain a sequence of current MRI images, the current MRI images of the sequence of current MRI images being associated with different time offsets of the multiple time offsets,
• wherein the data-consistency operation is based on differences between the MRI measurement datasets and synthesized MRI measurement datasets, the synthesized MRI measurement datasets being based on a k-space representation of a prior image of the multiple iterations, the at least one undersampling trajectory, and a sensitivity map associated with the receiver coil array, and
• wherein an input to the regularization operation comprises, for each iteration of the multiple iterations, a concatenation of multiple prior images obtained from a previous iteration of the multiple iterations, the multiple prior images being associated with the multiple time offsets.