Fast iterative algorithm for the reconstruction of multishot non-cartesian diffusion data

Merry Mani; Mathews Jacob; Vincent Magnotta; Jianhui Zhong

doi:10.1002/mrm.25486

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Fast iterative algorithm for the reconstruction of multishot non-cartesian diffusion data

Journal article

Peer reviewed

Fast iterative algorithm for the reconstruction of multishot non-cartesian diffusion data

Merry Mani, Mathews Jacob, Vincent Magnotta and Jianhui Zhong

Magnetic resonance in medicine, Vol.74(4), pp.1086-1094

10/2015

DOI: 10.1002/mrm.25486

PMID: 25323847

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Abstract

To accelerate the motion-compensated iterative reconstruction of multishot non-Cartesian diffusion data. The motion-compensated recovery of multishot non-Cartesian diffusion data is often performed using a modified iterative sensitivity-encoded algorithm. Specifically, the encoding matrix is replaced with a combination of nonuniform Fourier transforms and composite sensitivity functions, which account for the motion-induced phase errors. The main challenge with this scheme is the significantly increased computational complexity, which is directly related to the total number of composite sensitivity functions (number of shots × number of coils). The dimensionality of the composite sensitivity functions and hence the number of Fourier transforms within each iteration is reduced using a principal component analysis-based scheme. Using a Toeplitz-based conjugate gradient approach in combination with an augmented Lagrangian optimization scheme, a fast algorithm is proposed for the sparse recovery of diffusion data. The proposed simplifications considerably reduce the computation time, especially in the recovery of diffusion data from under-sampled reconstructions using sparse optimization. By choosing appropriate number of basis functions to approximate the composite sensitivities, faster reconstruction (close to 9 times) with effective motion compensation is achieved. The proposed enhancements can offer fast motion-compensated reconstruction of multishot diffusion data for arbitrary k-space trajectories.

Reproducibility of Results

Algorithms

Brain - anatomy & histology

Humans

Adult

Image Processing, Computer-Assisted - methods

Diffusion Magnetic Resonance Imaging - methods

Principal Component Analysis

Details

Title: Subtitle: Fast iterative algorithm for the reconstruction of multishot non-cartesian diffusion data
Creators: Merry Mani - Department of Electrical and Computer Engineering, University of Rochester, NewYork, USA
Mathews Jacob - Department of Electrical and Computer Engineering, University of Iowa, Iowa, USA
Vincent Magnotta - Department of Radiology, University of Iowa, Iowa, USA
Jianhui Zhong - Department of Biomedical Engineering, University of Rochester, NewYork, USA
Resource Type: Journal article
Publication Details: Magnetic resonance in medicine, Vol.74(4), pp.1086-1094
DOI: 10.1002/mrm.25486
PMID: 25323847
NLM abbreviation: Magn Reson Med
ISSN: 0740-3194
eISSN: 1522-2594
Publisher: United States
Grant note: R21 HL109710 / NHLBI NIH HHS
Language: English
Date published: 10/2015
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Psychiatry; Iowa Neuroscience Institute; Radiation Oncology
Record Identifier: 9984051565302771

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