Improving parallel imaging by jointly reconstructing multi‐contrast data

Abstract

JVC-GRAPPA takes advantage of additional spatial encoding from phase information and image similarity, and employs different sampling patterns across acquisitions. J-LORAKS achieves a more parsimonious low-rank representation of local k-space by considering multiple images as additional coils. Both approaches provide dramatic improvement in artifact and noise mitigation over conventional single-contrast parallel imaging reconstruction. Magn Reson Med 80:619-632, 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Wave‐LORAKS: Combining wave encoding with structured low‐rank matrix modeling for more highly accelerated 3D imaging

“…Specifically, because the LORAKS constraint is just regularization, it is easy to append additional regularization terms (e.g., TV or wavelet regularization) to the Wave‐LORAKS objective function in Equation . Another potentially interesting extension would be the combination of Wave encoding and LORAKS in the context of multi‐contrast imaging, since recent work has shown that LORAKS constraints can also be very beneficial when reconstructing multi‐contrast datasets …”

“…While autocalibrated LORAKS is inspired by all of these previous methods, it is a direct generalization of and most closely resembles the previous PRUNO approach . Similar autocalibration ideas have also been used in several subsequent publications . Another ingredient of our new implementation is the use of fast Fourier transforms (FFTs) for implementing matrix‐vector multiplications with high‐dimensional structured low‐rank matrices, as originally proposed by Ongie and Jacob.…”

Navigator‐based reacquisition and estimation of motion‐corrupted data: Application to multi‐echo spin echo for carotid wall MRI

“…Using randomized phase‐encoding within an echo train could allow T 2 mapping from undersampled data . Recent work on improving parallel imaging in multi‐contrast acquisitions is also relevant to these T 2 mapping scans …”

“…52 Recent work on improving parallel imaging in multi-contrast acquisitions is also relevant to these T 2 mapping scans. 53…”

High‐fidelity, high‐isotropic‐resolution diffusion imaging through gSlider acquisition with and T1 corrections and integrated ΔB0/Rx shim array

“…However, because of the prolonged scan time, shot-to-shot phase variations, and potential patient motion, multishot EPI continues to be a challenge in DWI. To mitigate these problems, previous studies combined multishot approaches with parallel imaging, 6,7 sparse or lowrank models, [8][9][10] joint reconstruction, [11][12][13][14][15] and simultaneous multislice (SMS) [16][17][18] to accelerate the acquisition and correct for shot-to-shot phase variations.…”