期刊
MAGNETIC RESONANCE IN MEDICINE
卷 77, 期 3, 页码 1021-1035出版社
WILEY
DOI: 10.1002/mrm.26182
关键词
parallel MRI; partial Fourier reconstruction; constrained reconstruction; low-rank matrix recovery
资金
- National Science Foundation (NSF) [CCF1350563]
- NIH [R01-NS089212, R24-MH106096, R01-EB019437]
- Division of Computing and Communication Foundations
- Direct For Computer & Info Scie & Enginr [1350563] Funding Source: National Science Foundation
Purpose: Parallel imaging and partial Fourier acquisition are two classical approaches for accelerated MRI. Methods that combine these approaches often rely on prior knowledge of the image phase, but the need to obtain this prior information can place practical restrictions on the data acquisition strategy. In this work, we propose and evaluate SENSELORAKS, which enables combined parallel imaging and partial Fourier reconstruction without requiring prior phase information. Theory and Methods: The proposed formulation is based on combining the classical SENSE model for parallel imaging data with the more recent LORAKS framework for MR image reconstruction using low-rank matrix modeling. Previous LORAKS-based methods have successfully enabled calibrationless partial Fourier parallel MRI reconstruction, but have been most successful with nonuniform sampling strategies that may be hard to implement for certain applications. By combining LORAKS with SENSE, we enable highly accelerated partial Fourier MRI reconstruction for a broader range of sampling trajectories, including widely used calibrationless uniformly undersampled trajectories. Results: Our empirical results with retrospectively undersampled datasets indicate that when SENSE-LORAKS reconstruction is combined with an appropriate k-space sampling trajectory, it can provide substantially better image quality at high-acceleration rates relative to existing state-of-the-art reconstruction approaches. Conclusion: The SENSE-LORAKS framework provides promising new opportunities for highly accelerated MRI. (C) 2016 International Society for Magnetic Resonance in Medicine
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