Electrical impedance tomography reconstruction through simulated annealing with total least square error as objective function

2012 ◽  
Author(s):  
Thiago de Castro Martins ◽  
Marcos de Sales Guerra Tsuzuki
Keyword(s):  
Simulated Annealing ◽  
Objective Function ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Least Square ◽  
Impedance Tomography ◽  
Tomography Reconstruction ◽  
Total Least Square

scholarly journals Interval Simulated Annealing applied to Electrical Impedance Tomography image reconstruction with fast objective function evaluation

2016 ◽  
Vol 72 (5) ◽  
pp. 1230-1243 ◽  
Author(s):  
Thiago de Castro Martins ◽  
Marcos de Sales Guerra Tsuzuki ◽  
Erick Dario León Bueno de Camargo ◽  
Raul Gonzalez Lima ◽  
Fernando Silva de Moura ◽  
...  
Keyword(s):  
Simulated Annealing ◽  
Image Reconstruction ◽  
Objective Function ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Function Evaluation ◽  
Impedance Tomography ◽  
Tomography Image ◽  
Electrical Impedance Tomography Image

scholarly journals A MATLAB-Based Boundary Data Simulator for Studying the Resistivity Reconstruction Using Neighbouring Current Pattern

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Tushar Kanti Bera ◽  
J. Nagaraju
Keyword(s):  
Electrical Impedance Tomography ◽  
Boundary Data ◽  
Electrical Impedance ◽  
Optical Tomography ◽  
Current Pattern ◽  
Impedance Tomography ◽  
Reconstruction Software ◽  
Tomography Reconstruction ◽  
Input Variables ◽  
Solver Performance

Phantoms are essentially required to generate boundary data for studying the inverse solver performance in electrical impedance tomography (EIT). A MATLAB-based boundary data simulator (BDS) is developed to generate accurate boundary data using neighbouring current pattern for assessing the EIT inverse solvers. Domain diameter, inhomogeneity number, inhomogeneity geometry (shape, size, and position), background conductivity, and inhomogeneity conductivity are all set as BDS input variables. Different sets of boundary data are generated by changing the input variables of the BDS, and resistivity images are reconstructed using electrical impedance tomography and diffuse optical tomography reconstruction software (EIDORS). Results show that the BDS generates accurate boundary data for different types of single or multiple objects which are efficient enough to reconstruct the resistivity images for assessing the inverse solver. It is noticed that for the BDS with 2048 elements, the boundary data for all inhomogeneities with a diameter larger than 13.3% of that of the phantom are accurate enough to reconstruct the resistivity images in EIDORS-2D. By comparing the reconstructed image with an original geometry made in BDS, it would be easier to study the inverse solver performance and the origin of the boundary data error can be identified.

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