This proof-of-concept study demonstrates a method to reduce CS reconstruction time for multi-image series (e.g. relaxometry mapping, multi-echo, or dynamic) by leveraging the similarity of data across the image series. The method consists of two components: a) re-using auto-calibrated coil sensitivity maps computed from data of the first image[0] and b) warm starting the iterative reconstruction of each image[i] using the final output from the reconstruction of the previous image[i-1] in the series. One insight is a ‘hybrid warm start’ created by combining the magnitude from the previous image[i-1] reconstruction and the phase of the back-projection of the current image[i].
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