Coil Compression for Accelerated Imaging with Cartesian Sampling

By Tao Zhang, John M. Pauly, Shreyas S. Vasanawala, Michael Lustig. Magnetic Resonance in Medicine, 2012

310 citations recorded by the source corpus.

MRI using receiver arrays with many coil elements can provide high signal‐to‐noise ratio and increase parallel imaging acceleration. At the same time, the growing number of elements results in larger datasets and more computation in the reconstruction. This is of particular concern in 3D acquisitions and in iterative reconstructions. Coil compression algorithms are effective in mitigating this problem by compressing data from many channels into fewer virtual coils. In Cartesian sampling there often are fully sampled k‐space dimensions. In this work, a new coil compression technique for Cartesian sampling is presented that exploits the spatially varying coil sensitivities in these nonsubsampled dimensions for better compression and computation reduction. Instead of directly compressing in k‐space, coil compression is performed separately for each spatial location along the fully sampled directions, followed by an additional alignment process that guarantees the smoothness of the virtual coil sensitivities. This important step provides compatibility with autocalibrating parallel imaging techniques. Its performance is not susceptible to artifacts caused by a tight imaging field‐of‐view. High quality compression of in vivo 3D data from a 32 channel pediatric coil into six virtual coils is demonstrated. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc.

Subfields: Atomic and Molecular Physics, and Optics, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/0711c5b4e5c62115537f3886980972820c8ed285

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In Atomic and Molecular Physics, and Optics

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

ESPIRiT — An Eigenvalue Approach to Autocalibrating Parallel MRI: Where SENSE meets GRAPPA (2014, background): “9) for an eight-channel coil compressed to six virtual channels [24].”
Simultaneous multislice (SMS) imaging techniques (2015, methodology): “Reduction ratios of 2–4 and higher have been demonstrated, with relatively minor penalty in SNR (79).”