• DocumentCode
    3140401
  • Title

    Electrical impedance tomography based on filter back projection improved by means method

  • Author

    Wang, Mingquan ; Zhao, Jinshuan ; Zhang, Shi ; Wang, Guohua

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • Volume
    1
  • fYear
    2010
  • fDate
    16-18 Oct. 2010
  • Firstpage
    218
  • Lastpage
    221
  • Abstract
    Electrical impedance tomography (EIT) is a new kind of noninvasive computer imaging technique. The imaging process of EIT is known as inverse problem, and the back projection algorithm is widely used to solve this problem in practice. However, the image can only be reconstructed with low resolution and interfered by artifacts using this algorithm. This paper proposes a new filter back projection algorithm for improving the quality of the image. Being different with other existing algorithms, this algorithm uses RL (Ramachandran and Lakshminarayanan) filter function to get ride of image artifacts and interference. Because the RL filtering function will take obvious oscillations while image reconstructing, the means method is utilized to modify the filter function in this paper. The results of numerous simulation experiments show the new algorithm can obtain much better resolution and less artifacts compared with existing back projection algorithms and filter algorithms using RL filter function.
  • Keywords
    electric impedance imaging; image reconstruction; image resolution; medical image processing; RL filter function; Ramachandran-Lakshminarayanan filter function; electrical impedance tomography; filter back projection algorithm; image reconstruction; image resolution; interference; noninvasive computer imaging technique; Back; Image reconstruction; Image resolution; Impedance; Projection algorithms; Tomography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Informatics (BMEI), 2010 3rd International Conference on
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4244-6495-1
  • Type

    conf

  • DOI
    10.1109/BMEI.2010.5639443
  • Filename
    5639443