Joint Image Reconstruction and Phase Corruption Maps Estimation in Multi-Shot Echo Planar Imaging

Multishot echo-planar imaging is a common strategy in diffusion Magnetic Resonance Imaging to reduce the artifacts caused by the long echo-trains in single-shot acquisitions. However, it suffers from shot-to-shot phase discrepancies associated to subject motion, which can notably degrade the quality of the reconstructed image. Consequently, some type of motion-induced phases error correction needs to be incorporated into the reconstruction process. In this paper we focus on ridig motion induced errors, which have proved to corrupt the shots with linear phase maps. By incorporating this prior knowledge, we propose a maximum likelihood formulation that estimates both the parameters that characterize the linear phase maps and the reconstructed image. In order to make the problem tractable, we follow a greedy iterative procedure that alternates between the estimation of each of them. Simulation data are used to illustrate the performance of the method against state-of-the-art alternatives.

[1]  Johnpauly A k-Space Analysis of Small-Tip-Angle Excitation , 2012 .

[2]  P. Boesiger,et al.  SENSE: Sensitivity encoding for fast MRI , 1999, Magnetic resonance in medicine.

[3]  Jia-Hong Gao,et al.  DWI using navigated interleaved multishot EPI with realigned GRAPPA reconstruction , 2016, Magnetic resonance in medicine.

[4]  Mathews Jacob,et al.  Multi‐shot sensitivity‐encoded diffusion data recovery using structured low‐rank matrix completion (MUSSELS) , 2017, Magnetic resonance in medicine.

[5]  Karla L Miller,et al.  Nonlinear phase correction for navigated diffusion imaging , 2003, Magnetic resonance in medicine.

[6]  P. Boesiger,et al.  Advances in sensitivity encoding with arbitrary k‐space trajectories , 2001, Magnetic resonance in medicine.

[7]  Diego Hernando,et al.  Motion-Induced Phase Error Estimation and Correction in 3D Diffusion Tensor Imaging , 2011, IEEE Transactions on Medical Imaging.

[8]  J C Gore,et al.  Analysis and correction of motion artifacts in diffusion weighted imaging , 1994, Magnetic resonance in medicine.

[9]  P Boesiger,et al.  Influence of SENSE on image properties in high‐resolution single‐shot echo‐planar DTI , 2006, Magnetic resonance in medicine.

[10]  Leslie Ying,et al.  Joint image reconstruction and sensitivity estimation in SENSE (JSENSE) , 2007, Magnetic resonance in medicine.

[11]  Jin Hyung Lee,et al.  DWI of the spinal cord with reduced FOV single‐shot EPI , 2008, Magnetic resonance in medicine.

[12]  Allen W. Song,et al.  A robust multi-shot scan strategy for high-resolution diffusion weighted MRI enabled by multiplexed sensitivity-encoding (MUSE) , 2013, NeuroImage.

[13]  Jeffrey A. Fessler,et al.  Accelerated Regularized Estimation of MR Coil Sensitivities Using Augmented Lagrangian Methods , 2013, IEEE Transactions on Medical Imaging.

[14]  E Brian Welch,et al.  Ghost reduction in echo‐planar imaging by joint reconstruction of images and line‐to‐line delays and phase errors , 2017, Magnetic resonance in medicine.

[15]  Zhe Zhang,et al.  Interleaved EPI diffusion imaging using SPIRiT‐based reconstruction with virtual coil compression , 2018, Magnetic resonance in medicine.

[16]  Justin P. Haldar,et al.  Navigator-Free EPI Ghost Correction With Structured Low-Rank Matrix Models: New Theory and Methods , 2017, IEEE Transactions on Medical Imaging.