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Clinical Imaging of Microwave Mammography
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A fast parallel solver for the forward problem in electrical impedance tomography.

Markus Jehl, Andreas Dedner, Timo Betcke

    IEEE Transactions on Bio-Medical Engineering
    |July 29, 2014
    PubMed
    Summary
    This summary is machine-generated.

    A new parallel solver significantly speeds up Electrical Impedance Tomography (EIT) forward computations. This advancement enables faster stroke detection using EIT, improving diagnostic capabilities for ischemic and hemorrhagic stroke.

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    Area of Science:

    • Biomedical Engineering
    • Medical Imaging
    • Computational Science

    Background:

    • Electrical Impedance Tomography (EIT) offers noninvasive stroke detection.
    • Accurate forward modeling is crucial for EIT image reconstruction.
    • Large finite-element meshes (10M+ elements) are required for stroke EIT, leading to long computation times.

    Purpose of the Study:

    • To develop and implement a parallel forward solver for EIT.
    • To reduce the computational time for EIT forward modeling and Jacobian matrix calculation.
    • To enhance the feasibility of EIT for clinical applications, particularly stroke diagnosis.

    Main Methods:

    • Implementation of a parallel forward solver using the Dune-Fem C++ library.
    • Utilizing a computer cluster for parallel processing of EIT forward computations.
    • Comparison of iterative solvers with multigrid preconditioning against direct solvers.

    Main Results:

    • The parallel solver significantly reduces computation time for EIT forward solutions and Jacobian matrices.
    • A 15-million element mesh EIT application with 30 electrodes was computed in under 15 minutes.
    • Iterative solvers with multigrid preconditioning outperformed direct solvers for this application.

    Conclusions:

    • The developed parallel solver is a valuable tool for EIT simulation studies and high-precision applications.
    • Reduced computation time makes EIT a more practical and accessible tool for stroke detection.
    • The software is freely available, promoting further research and development in EIT.