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Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
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EIT image regularization by a new Multi-Objective Simulated Annealing algorithm

Thiago Castro Martins, Marcos Sales Guerra Tsuzuki

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |January 7, 2016
    PubMed

    Abstract:

    Multi-Objective Optimization can be used to produce regularized Electrical Impedance Tomography (EIT) images where the weight of the regularization term is not known a priori. This paper proposes a novel Multi-Objective Optimization algorithm based on Simulated Annealing tailored for EIT image reconstruction. Images are reconstructed from experimental data and compared with images from other Multi and Single Objective optimization methods. A significant performance enhancement from traditional techniques can be inferred from the results.

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