Abstract
An image reconstruction method is proposed based on Lagrange-Newton method for electrical impedance tomography (EIT) and ultrasound tomography (UT) dual-modality imaging. Since the change in conductivity distribution is usually accompanied with the change in acoustic impedance distribution, the reconstruction targets of EIT and UT are unified to the conductivity difference using the same mesh model. Some background medium distribution information obtained from ultrasound transmission and reflection measurements can be used to construct a hard constraint about the conductivity difference distribution. Then, the EIT/UT dual-modality inverse problem is constructed by an equality constraint equation, and the Lagrange multiplier method combining Newton-Raphson iteration is used to solve the EIT/UT dual-modality inverse problem. The numerical and experimental results show that the proposed dual-modality image reconstruction method has a better performance than the single-modality EIT method and is more robust to the measurement noise.
Highlights
Electrical impedance tomography (EIT) is a non-invasive technique to reconstruct the distribution of the media within a closed vessel based on the differences of their conductivities
Considering that the selection of regularization parameters has a great influence on the imaging results, the regularization parameters in all methods are empirically selected in the range of 10−6 to 10−3, and the one that reached the most similar result to the real model was used in the comparison [45]
The reconstruction results from EIT/ultrasound tomography (UT) dual-modality method is simplified as UT dual-modality imaging method (UET) in the paper
Summary
Electrical impedance tomography (EIT) is a non-invasive technique to reconstruct the distribution of the media within a closed vessel based on the differences of their conductivities. In 2008, Steiner et al proposed an EIT/ultrasound reflection tomography (URT) dual-modality imaging method for small object detection in biomedical applications, where the measurement information from URT was used to construct the weighted regularization matrix in EIT inverse problem [30]. In 2015, Teniou et al proposed an electrical resistance tomography (ERT)/URT dual-modality imaging method to detect the small lesions in biological soft tissue, where the measurements from URT was used as hard constraints during the EIT image reconstruction process [32]. In 2018, Liang et al proposed a shape-based EIT/URT dual-modality imaging method, where some accurate boundaries information about the inclusions detected from URT are used to improve the EIT inclusion boundary reconstruction accuracy [34]. To test the performance of the proposed dual-modality imaging method, the numerical and experimental tests are conducted
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