title: Accelerated reconstruction of electrical impedance tomography images via patch based sparse representation.
abstract: Electrical impedance tomography (EIT) reconstruction is a nonlinear and ill-posed problem. Exact reconstruction of an EIT image inverts a high dimensional mathematical model to calculate the conductivity field, which causes significant problems regarding that the computational complexity will reduce the achievable frame rate, which is considered as a major advantage of EIT imaging. The single-step method, state estimation method, and projection method were always used to accelerate reconstruction process. The basic principle of these methods is to reduce computational complexity. However, maintaining high resolution in space together with not much cost is still challenging, especially for complex conductivity distribution. This study proposes an idea to accelerate image reconstruction of EIT based on compressive sensing (CS) theory, namely, CSEIT method. The novel CSEIT method reduces the sampling rate through minimizing redundancy in measurements, so that detailed information of reconstruction is not lost. In order to obtain sparse solution, which is the prior condition of signal recovery required by CS theory, a novel image reconstruction algorithm based on patch-based sparse representation is proposed. By applying the new framework of CSEIT, the data acquisition time, or the sampling rate, is reduced by more than two times, while the accuracy of reconstruction is significantly improved.
authors.affiliation: School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, People's Republic of China.
authors.forename: Qi
authors.initials: Q
authors.lastname: Wang
authors.affiliation: School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, People's Republic of China.
authors.forename: Zhijie
authors.initials: Z
authors.lastname: Lian
authors.affiliation: School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, People's Republic of China.
authors.forename: Jianming
authors.initials: J
authors.lastname: Wang
authors.affiliation: Tianjin Chest Hospital, Tianjin 300222, People's Republic of China.
authors.forename: Qingliang
authors.initials: Q
authors.lastname: Chen
authors.affiliation: School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, People's Republic of China.
authors.forename: Yukuan
authors.initials: Y
authors.lastname: Sun
authors.affiliation: School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, People's Republic of China.
authors.forename: Xiuyan
authors.initials: X
authors.lastname: Li
authors.affiliation: School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, People's Republic of China.
authors.forename: Xiaojie
authors.initials: X
authors.lastname: Duan
authors.affiliation: School of Electrical Engineering & Automation, Tianjin University, Tianjin 300072, People's Republic of China.
authors.forename: Ziqiang
authors.initials: Z
authors.lastname: Cui
authors.affiliation: School of Electrical Engineering & Automation, Tianjin University, Tianjin 300072, People's Republic of China.
authors.forename: Huaxiang
authors.initials: H
authors.lastname: Wang