Development of Electromagnetic Tomography Models

This research aims to implement the development of electromagnetic tomography models to provide accurate and reliable raw data for image reconstruction. Through in-depth study and analysis of electromagnetic tomography technology, we will explore methods to optimize the model construction process by implementing finite element method (FEM) solvers and boundary condition handlers to improve the precision and effectiveness of image reconstruction. Additionally, we will incorporate advanced data acquisition techniques such as multi-frequency excitation protocols and signal processing algorithms to gather comprehensive raw data. This data will be integrated with electromagnetic tomography models through matrix assembly routines and inverse problem solvers to achieve more complete and accurate image reconstruction results. Our implementation approach includes developing modular code architecture with key functions for forward modeling, sensitivity matrix calculation, and iterative reconstruction algorithms. These efforts will contribute new methodologies to electromagnetic tomography technology, providing enhanced solutions for image reconstruction in medical imaging and industrial nondestructive testing applications.