Higher order total variation regularization for EIT reconstruction.

Electrical impedance tomography (EIT) attempts to reveal the conductivity distribution of a domain based on the electrical boundary condition. This is an ill-posed inverse problem; its solution is very unstable. Total variation (TV) regularization is one of the techniques commonly employed to stabil...

Descripción completa

Detalles Bibliográficos
Publicado en:Medical & Biological Engineering & Computing Vol. 56; no. 8; pp. 1367 - 1379
Autores principales: Gong, Bo, Schullcke, Benjamin, Krueger-Ziolek, Sabine, Zhang, Fan, Mueller-Lisse, Ullrich, Moeller, Knut
Formato: equations & formulas pictorial research tables/charts Journal Article
Publicado: Springer Nature Aug2018
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=130773120&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 130773120
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        01400118
        PO0
      jtl: Medical & Biological Engineering & Computing
      issn: 01400118
      maglogo: N
    pubinfo:
      dt: Aug2018
      vid: 56
      iid: 8
      pid: 237
      pub: Springer Nature
      place: New York, New York
    artinfo:
      ui:
        130773120
        130773120
        NLM29308547
        130773120
        10.1007/s11517-017-1782-z
        NLM29308547
        130773120
      ppf: 1367
      ppct: 12
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
      tig:
        atl: Higher order total variation regularization for EIT reconstruction.
      aug:
        au:
          Gong, Bo
          Schullcke, Benjamin
          Krueger-Ziolek, Sabine
          Zhang, Fan
          Mueller-Lisse, Ullrich
          Moeller, Knut
        affil: Institute of Technical Medicine, Furtwangen University, VS-Schwenningen, Germany
      sug:
        subj:
          Tomography
          Electric Impedance
          Image Processing, Computer Assisted
          Lung Anatomy and Histology
          Systems Analysis
          Computer Simulation
          Algorithms
          Finite Element Analysis
          Human
      ab: Electrical impedance tomography (EIT) attempts to reveal the conductivity distribution of a domain based on the electrical boundary condition. This is an ill-posed inverse problem; its solution is very unstable. Total variation (TV) regularization is one of the techniques commonly employed to stabilize reconstructions. However, it is well known that TV regularization induces staircase effects, which are not realistic in clinical applications. To reduce such artifacts, modified TV regularization terms considering a higher order differential operator were developed in several previous studies. One of them is called total generalized variation (TGV) regularization. TGV regularization has been successively applied in image processing in a regular grid context. In this study, we adapted TGV regularization to the finite element model (FEM) framework for EIT reconstruction. Reconstructions using simulation and clinical data were performed. First results indicate that, in comparison to TV regularization, TGV regularization promotes more realistic images. Graphical abstract Reconstructed conductivity changes located on selected vertical lines. For each of the reconstructed images as well as the ground truth image, conductivity changes located along the selected left and right vertical lines are plotted. In these plots, the notation GT in the legend stands for ground truth, TV stands for total variation method, and TGV stands for total generalized variation method. Reconstructed conductivity distributions from the GREIT algorithm are also demonstrated.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N