Abstract
Abstract
A multi-parameter joint reconstruction method is proposed for electrical impedance tomography (EIT) and ultrasonic transmission tomography (UTT) dual-modality tomography based on statistical joint inversion framework. The inherent correlation of two imaging modalities is that the conductivity and sound speed parameters share the same structure, which can be defined by the structural similarity of the spatial distributions of conductivity and sound speed. The structural similarity between conductivity and sound speed is quantitatively characterized by a joint prior model with total variation and cross-gradient functionals. The multi-parameter joint reconstruction problem is constructed by Bayesian joint inverse model, and solved by maximum a posterior method with alternate solution strategy. Numerical and experimental tests are carried out to evaluate the performance of the proposed method. The results show that the proposed EIT/UTT dual-modality tomography method with structural similarity promoting can improve the reconstruction accuracy of conductivity and sound speed compared with the traditional single-modality EIT and UTT methods.
Funder
Academy of Finland
National Natural Science Foundation of China
Subject
Applied Mathematics,Computer Science Applications,Mathematical Physics,Signal Processing,Theoretical Computer Science
Cited by
1 articles.
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