title: Modified sparse regularization for electrical impedance tomography.
abstract: Electrical impedance tomography (EIT) aims to estimate the electrical properties at the interior of an object from current-voltage measurements on its boundary. It has been widely investigated due to its advantages of low cost, non-radiation, non-invasiveness, and high speed. Image reconstruction of EIT is a nonlinear and ill-posed inverse problem. Therefore, regularization techniques like Tikhonov regularization are used to solve the inverse problem. A sparse regularization based on L1 norm exhibits superiority in preserving boundary information at sharp changes or discontinuous areas in the image. However, the limitation of sparse regularization lies in the time consumption for solving the problem. In order to further improve the calculation speed of sparse regularization, a modified method based on separable approximation algorithm is proposed by using adaptive step-size and preconditioning technique. Both simulation and experimental results show the effectiveness of the proposed method in improving the image quality and real-time performance in the presence of different noise intensities and conductivity contrasts.
authors.affiliation: School of Aeronautical Automation, Civil Aviation University of China, Tianjin 300300, China.
authors.forename: Wenru
authors.initials: W
authors.lastname: Fan
authors.affiliation: School of Electrical and Automation Engineering, Tianjin University, Tianjin 300072, China.
authors.forename: Huaxiang
authors.initials: H
authors.lastname: Wang
authors.affiliation: School of Aeronautical Automation, Civil Aviation University of China, Tianjin 300300, China.
authors.forename: Qian
authors.initials: Q
authors.lastname: Xue
authors.affiliation: School of Electrical and Automation Engineering, Tianjin University, Tianjin 300072, China.
authors.forename: Ziqiang
authors.initials: Z
authors.lastname: Cui
authors.affiliation: School of Electrical and Automation Engineering, Tianjin University, Tianjin 300072, China.
authors.forename: Benyuan
authors.initials: B
authors.lastname: Sun
authors.affiliation: School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, China.
authors.forename: Qi
authors.initials: Q
authors.lastname: Wang