Compressed sensing with PCA based coil compression is a promising way to obtain high quality radial perfusion images without incurring the high computation cost and memory requirements associated with large multi-coil arrays
Array compression for MRI with large coil arrays
β Scribed by Martin Buehrer; Klaas P. Pruessmann; Peter Boesiger; Sebastian Kozerke
- Book ID
- 102953959
- Publisher
- John Wiley and Sons
- Year
- 2007
- Tongue
- English
- Weight
- 860 KB
- Volume
- 57
- Category
- Article
- ISSN
- 0740-3194
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β¦ Synopsis
Abstract
Arrays with large numbers of independent coil elements are becoming increasingly available as they provide increased signalβtoβnoise ratios (SNRs) and improved parallel imaging performance. Processing of data from a large set of independent receive channels is, however, associated with an increased memory and computational load in reconstruction. This work addresses this problem by introducing coil array compression. The method allows one to reduce the number of datasets from independent channels by combining all or partial sets in the time domain prior to image reconstruction. It is demonstrated that array compression can be very effective depending on the size of the region of interest (ROI). Based on 2D in vivo data obtained with a 32βelement phasedβarray coil in the heart, it is shown that the number of channels can be compressed to as few as four with only 0.3% SNR loss in an ROI encompassing the heart. With twofold parallel imaging, only a 2% loss in SNR occurred using the same compression factor. Magn Reson Med 57:1131β1139, 2007. Β© 2007 WileyβLiss, Inc.
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