A Novel Method to Mitigate Real-Imaginary Image Imbalance in Microwave Tomography

Area of Science:

• Electromagnetics and Applied Physics
• Biomedical Imaging
• Computational Electromagnetics

Background:

• Microwave tomography (MWT) typically reconstructs the real part of permittivity more accurately than the imaginary part.
• This imbalance limits the fidelity of MWT imaging, particularly for biological tissues where both components are crucial.

Purpose of the Study:

• To develop and validate a method that mitigates the imbalance between reconstructed complex permittivity components in MWT.
• To enhance the overall accuracy and reliability of MWT image recovery for biomedical applications.

Main Methods:

• The proposed method represents complex permittivity as a weighted sum of preselected, expected permittivity values.
• A Gauss-Newton algorithm is utilized to determine the optimal permittivity weights.
• The technique was tested using simulated and experimental data from various biomedical phantoms.

Main Results:

• The method successfully achieved excellent reconstruction of both real and imaginary permittivity components.
• Balanced reconstruction accuracy was observed across different scenarios and phantom types.
• The proposed approach significantly improved the overall image recovery compared to traditional methods.

Conclusions:

• The developed weighted-sum approach effectively addresses the real/imaginary component imbalance in MWT.
• This technique offers a promising solution for more accurate and reliable biomedical imaging using microwave tomography.
• Future work can explore broader applications and more complex phantom scenarios.