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Abstract #3348

Reconstruction of TOF Images from Undersampled K-Data Using SENSE, GRAPPA, CS, CS-SENSE, SPIRiT, and L1-SPIRiT

Jerome Yerly1, 2, Michel Louis Lauzon, 23, Richard Frayne, 23

1Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada; 2Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, AB, Canada; 3Departments of Radiology and Clinical Neurosciences, University of Calgary, Calgary, AB, Canada

Recent advances in image reconstruction from sparsely sampled k-space data, such as CS and parallel MR imaging, provide potential solutions to enable visualization of small cerebral vessels without increasing the total acquisition time. In this study, we investigated and compared SENSE, GRAPPA, CS, SPIRiT, CS-SENSE, and L1-SPIRiT techniques to accelerate time-of-flight 3-T MR imaging. The reconstructions involving an L1-norm regularization procedure (i.e., CS, CS-SENSE, and L1-SPIRiT) resulted in lower aliasing interference, but also less conspicuous small cerebral vessels due to blurring. The auto-calibrating techniques (i.e., GRAPPA, SPIRiT, and L1-SPIRiT) exhibited less sensitivity artifacts and most reliably depicted small vessels.