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

Area of Science:

• Biomedical Engineering
• Computational Physics
• Medical Imaging

Background:

• Electrical impedance tomography (EIT) reconstructs internal conductivity distributions using boundary measurements.
• Traditional EIT reconstruction often involves computationally intensive optimization, combining simulated annealing (SA) and finite element method (FEM).
• High computational cost limits the practical application of SA-FEM for EIT.

Purpose of the Study:

• To develop a computationally efficient approach for EIT image reconstruction.
• To reduce the high computational burden associated with conventional SA-FEM methods in EIT.
• To validate a novel EIT reconstruction strategy using experimental data.

Main Methods:

• The study proposes a new EIT reconstruction method combining simulated annealing (SA) with partial objective function evaluations.
• Overdetermined linear systems are utilized to approximate objective function values efficiently.
• The proposed method is evaluated using experimental EIT data.

Main Results:

• The novel approach significantly reduces the computational cost of EIT reconstruction compared to traditional SA-FEM methods.
• The method demonstrates effective EIT image reconstruction capabilities when assessed with experimental data.
• Performance is comparable to or better than existing EIT reconstruction techniques.

Conclusions:

• The proposed SA-based EIT reconstruction with partial objective function evaluations offers a viable and computationally efficient alternative.
• This method enhances the practicality of EIT for various applications by addressing computational limitations.
• Further research can explore optimizations and applications of this technique in medical imaging.