Electrical Impedance Tomography (EIT) has been a heatedly discussed medical imaging technique for its functional imaging and safety with easy operation and relatively low cost. It is basically developed from different electrical impedance of different tissues in a living body under different functional states, enabling the exploration of internal body structures and functions.

However, electrical impedance tomography restruction is categorized in some non-linear inverse problems that are severely ill-conditioning, resulting in poor resolution and extremely high sensitivity to modeling errors, which prevents it from practical use.

Recently, the research group led by CAS Academician DU Jiangfeng at Key Laboratory of Microscale Magnetic Resonance of University of Science and Technology of China of Chinese Academy of Sciences (CAS) realized EIT with high resolution and robustness, which will open a new window for clinical medicine. The findings were published in IEEE Transactions on Medical Imaging.

In this study, the researchers designed a new algorithm for electrical impedance tomography with utilization of recent parametric level set methods and prior information in clinical medicine, and realized high resolution in image restruction.

Loads of simulated experiments proved that such algorithm is both effective and feasible, confirming its capability of generating images with high resolution and robustness confronted with ubiquitous modeling errors, and setting modes of parameter optimization and the like.

This study will enable the EIT to be applied in more practical fields such as pulmonary clinical electrical impedance tomography.

The study was sponsored by the Ministry of Science and Technology, National Natural Science Foundation of China, Chinese Academy of Sciences and Anhui Province.