Multi-dimensional radial self-navigation with non-linear reconstruction for free-breathing coronary MRI

The main challenge for cardiac MRI is motion. To account for respiratory motion, k-space-based self- navigation approaches have recently been introduced [1]. We took self-navigation to the next level by exploiting an image-based beat-to-beat respiratory motion correction algorithm [2] for coronary MRI. For each heartbeat, under-sampled sub-images (sub-sets of data used for final image reconstruction) are reconstructed and multi-dimensional respiratory motion parameters extracted. Non-linear reconstruction (related to Compressed Sensing) is proposed to generate the motion-corrected sub-images and the results are compared to those of a more conventional approach [3]. These studies include computer simulations and initial 3T human in vivo data.


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Book of abstract of the 28th Annual Scientific Meeting of the European Society for Magnetic Resonance in Medecine and Biology, 24, 1, 267-268
Presented at:
28th Annual Scientific Meeting of the European Society for Magnetic Resonance in Medecine and Biology, Leipzig, October 6-8, 2011
Year:
2011
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 Record created 2011-07-04, last modified 2018-01-28

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