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Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
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Accelerated MR-STAT Reconstructions Using Sparse Hessian Approximations.

Oscar van der Heide, Alessandro Sbrizzi, Cornelis A T van den Berg

    IEEE Transactions on Medical Imaging
    |August 4, 2020
    PubMed
    Summary
    This summary is machine-generated.

    MR-STAT, a quantitative magnetic resonance imaging method, now reconstructs tissue parameter maps faster. Exploiting Hessian matrix sparsity in its reconstruction algorithm reduces scan times by tenfold.

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    Area of Science:

    • Magnetic Resonance Imaging (MRI)
    • Quantitative Imaging
    • Biophysics

    Background:

    • Quantitative magnetic resonance imaging (qMRI) enables multi-parametric tissue mapping.
    • MR-STAT is a framework for qMRI using single, short scans.
    • Previous MR-STAT versions utilized a matrix-free Gauss-Newton algorithm.

    Purpose of the Study:

    • To analyze the Hessian matrix structure within the MR-STAT reconstruction algorithm.
    • To identify conditions enabling sparse Hessian matrix approximations.
    • To accelerate MR-STAT image reconstruction times.

    Main Methods:

    • Analysis of the Hessian matrix structure related to spin system dynamics.
    • Derivation of conditions for Hessian matrix sparsity.
    • Implementation of sparse matrix techniques within the Gauss-Newton algorithm for MR-STAT.
    • Testing with Cartesian sampling patterns and smooth radiofrequency pulses.

    Main Results:

    • Conditions for a sparse Hessian matrix in MR-STAT were derived.
    • Exploiting Hessian sparsity reduced MR-STAT reconstruction times by approximately an order of magnitude.
    • The acceleration was demonstrated for Cartesian sampling with smooth RF trains.

    Conclusions:

    • The developed method significantly enhances the computational efficiency of MR-STAT.
    • This acceleration makes high-resolution, multi-parametric qMRI more accessible.
    • Sparsity exploitation is a key strategy for optimizing MR-STAT performance.