Acceleration of FEM-based transfer matrix computation for forward and inverse problems of electrocardiography.

The distributions of transmembrane voltage (TMV) within the cardiac tissue are linearly connected with the patient's body surface potential maps (BSPMs) at every time instant. The matrix describing the relation between the respective distributions is referred to as the transfer matrix. This matrix c...

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Publicado en:Medical & Biological Engineering & Computing Vol. 47; no. 12; pp. 1229 - 1237
Autores principales: Farina D, Jiang Y, Dössel O, Farina, Dmytro, Jiang, Y, Dössel, O
Formato: research Journal Article
Publicado: Springer Nature Dec2009
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Dec2009
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      pub: Springer Nature
      place: New York, New York
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        atl: Acceleration of FEM-based transfer matrix computation for forward and inverse problems of electrocardiography.
      aug:
        au:
          Farina D
          Jiang Y
          Dössel O
          Farina, Dmytro
          Jiang, Y
          Dössel, O
        affil: CST Computer Simulation Technology AG, Darmstadt, Germany
      sug:
        subj:
          Body Surface Potential Mapping Methods
          Electrocardiography
          Evaluation Research
          Finite Element Analysis
          Models, Anatomic
      ab: The distributions of transmembrane voltage (TMV) within the cardiac tissue are linearly connected with the patient's body surface potential maps (BSPMs) at every time instant. The matrix describing the relation between the respective distributions is referred to as the transfer matrix. This matrix can be employed to carry out forward calculations in order to find the BSPM for any given distribution of TMV inside the heart. Its inverse can be used to reconstruct the cardiac activity non-invasively, which can be an important diagnostic tool in the clinical practice. The computation of this matrix using the finite element method can be quite time-consuming. In this work, a method is proposed allowing to speed up this process by computing an approximate transfer matrix instead of the precise one. The method is tested on three realistic anatomical models of real-world patients. It is shown that the computation time can be reduced by 50% without loss of accuracy.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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