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Abstract #1205

Accelerated z-Spectrum Imaging

Melany Mclean1, Matthew Ethan MacDonald2, R. Marc Lebel1,2,3, Mathieu Boudreau4, and Bruce Pike2

1Biomedical Engineering, University of Calgary, Calgary, AB, Canada, 2Radiology, University of Calgary, Calgary, AB, Canada, 3GE Healthcare, Calgary, AB, Canada, 4Montreal Neurological Institute, McGill University, Montreal, QC, Canada

Long acquisition times preclude many potential applications of z-spectrum based imaging techniques, and have hindered their widespread use. Using SparseSENSE, a combined parallel imaging and compressed sensing acceleration technique, we present a method to reduce the acquisition time of z-spectrum images by a factor of 16. Z-spectrum images have been retrospectively undersampled to simulate 2-20× acceleration factors. Sparsifying reconstruction algorithms enable high quality image reconstructions for ambitious acceleration factors and are shown to maintain z-spectrum accuracy.

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