DOI: 10.3390/s26216830 ISSN: 1424-8220

A Joint Measurement and Sensitivity Enhancement Method for Improving EIT Image Reconstruction Quality

Yanlong Li, Xiaonan Wei, Bowen Xu, Honghao Qu, Shihong Yue

Electrical impedance tomography (EIT) is widely used in industrial and biomedical applications, but weak central sensitivity can obscure internal targets. This study proposes a joint enhancement (JE) method combining center-residual feedback with regional sensitivity-based measurement enhancement. Reconstructed peripheral structures are used to approximate unavailable target-free measurements and iteratively extract central-target residual information. Regional sensitivity decomposition enhances the central measurement component, which is reconstructed using Tikhonov regularization and integrated with the peripheral structure. Tests on five simulated thoracic models and five saline-tank configurations show that JE achieves the highest correlation coefficient (CC) and lowest relative error (RE) among the four compared methods. Relative to the initial linear back-projection reconstruction, JE increases mean CC by approximately 15.48% and reduces mean RE by 25.87% in simulation; the corresponding experimental improvements are 21.68% and 12.82%, respectively. These results support improved central-target recovery for the tested configurations. The proposed method as a whole has the potential to be applied to general EIT processes.

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