Image Reconstruction using Simulated Annealing Algorithm in EIT
Ho-Chan Kim, Chang-Jin Boo, Yoon-Joon Lee
Abstract
Ho-Chan Kim, Chang-Jin Boo, Yoon-Joon Lee
Abstract
Abstract: In electrical impedance tomography (EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically, the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents a simulated annealing technique as a statistical reconstruction algorithm for the solution of the static EIT inverse problem. Computer simulations with 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved as compared to that of the mNR algorithm at the expense of increased computational burden.
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Abstract: In electrical impedance tomography (EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically, the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents a simulated annealing technique as a statistical reconstruction algorithm for the solution of the static EIT inverse problem. Computer simulations with 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved as compared to that of the mNR algorithm at the expense of increased computational burden.
Key concepts: Electrical impedance tomography, Algorithm, Inverse problem, Iterative reconstruction, Simulated annealing, Tomography, Electrical resistivity tomography, Computer science