Adaptive techniques in electrical impedance tomography reconstruction

被引:9
|
作者
Li, Taoran [1 ]
Isaacson, David [2 ]
Newell, Jonathan C. [3 ]
Saulnier, Gary J. [1 ]
机构
[1] Rensselaer Polytech Inst, Dept Elect Comp & Syst Engn, Troy, NY 12180 USA
[2] Rensselaer Polytech Inst, Dept Math Sci, Troy, NY 12180 USA
[3] Rensselaer Polytech Inst, Dept Biomed Engn, Troy, NY 12180 USA
关键词
electrical impedance tomography; adaptive image reconstruction; Kaczmarz method; optimal current patterns; reconstruction accuracy; MESH REFINEMENT; EIT;
D O I
10.1088/0967-3334/35/6/1111
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
We present an adaptive algorithm for solving the inverse problem in electrical impedance tomography. To strike a balance between the accuracy of the reconstructed images and the computational efficiency of the forward and inverse solvers, we propose to combine an adaptive mesh refinement technique with the adaptive Kaczmarz method. The iterative algorithm adaptively generates the optimal current patterns and a locally-refined mesh given the conductivity estimate and solves for the unknown conductivity distribution with the block Kaczmarz update step. Simulation and experimental results with numerical analysis demonstrate the accuracy and the efficiency of the proposed algorithm.
引用
收藏
页码:1111 / 1124
页数:14
相关论文
共 50 条
  • [21] Generalized linearization techniques in electrical impedance tomography
    Hyvonen, Nuutti
    Mustonen, Lauri
    NUMERISCHE MATHEMATIK, 2018, 140 (01) : 95 - 120
  • [22] Generalized linearization techniques in electrical impedance tomography
    Nuutti Hyvönen
    Lauri Mustonen
    Numerische Mathematik, 2018, 140 : 95 - 120
  • [23] Adaptive Lp Regularization for Electrical Impedance Tomography
    Li, Jia
    Yue, Shihong
    Ding, Mingliang
    Cui, Ziqiang
    Wang, Huaxiang
    IEEE SENSORS JOURNAL, 2019, 19 (24) : 12297 - 12305
  • [24] Image Reconstruction for Electrical Impedance Tomography Using Enhanced Adaptive Group Sparsity With Total Variation
    Yang, Yunjie
    Wu, Hancong
    Jia, Jiabin
    IEEE SENSORS JOURNAL, 2017, 17 (17) : 5589 - 5598
  • [25] Logistic regression in image reconstruction in electrical impedance tomography
    Kozlowski, Edward
    Rymarczyk, Tomasz
    Klosowski, Grzegorz
    Cieplak, Tomasz
    PRZEGLAD ELEKTROTECHNICZNY, 2020, 96 (05): : 95 - 98
  • [26] Three-dimensional reconstruction in electrical impedance tomography
    Liu, W.P.
    Hua, P.
    Webster, J.G.
    Clinical Physics and Physiological Measurement, 1988, 9 (SUPPL. A): : 131 - 135
  • [27] COMPARING RECONSTRUCTION ALGORITHMS FOR ELECTRICAL-IMPEDANCE TOMOGRAPHY
    YORKEY, TJ
    WEBSTER, JG
    TOMPKINS, WJ
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 1987, 34 (11) : 843 - 852
  • [28] UNet model in image reconstruction for electrical impedance tomography
    Maciura, Lukasz
    Wojcik, Dariusz
    Rosa, Wojciech
    Rymarczyk, Tomasz
    Maj, Michal
    PRZEGLAD ELEKTROTECHNICZNY, 2022, 98 (04): : 123 - 126
  • [29] Simultaneous Reconstruction of Conductivity and Permittivity in Electrical Impedance Tomography
    Zhu, Zengyan
    Wang, Yutao
    PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019), 2019, : 3211 - 3215
  • [30] Directional Algebraic Reconstruction Technique for Electrical Impedance Tomography
    Kim, Ji Hoon
    Choi, Bong Yeol
    Ijaz, Umer Zeeshan
    Kim, Bong Seok
    Kim, Sin
    Kim, Kyung Youn
    JOURNAL OF THE KOREAN PHYSICAL SOCIETY, 2009, 54 (04) : 1439 - 1447