• DocumentCode
    1740596
  • Title

    Noninvasive localization of myocardial infarction by means of a 3D heart-model based inverse imaging approach

  • Author

    Li, Guanglin ; He, Bin

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Illinois Univ., Chicago, IL, USA
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    891
  • Abstract
    It is of significance to localize sites of myocardial infarction (MI) noninvasively. The authors have investigated the feasibility of localizing MI sites from body surface ECGs in terms of a heart-model based new inverse solution. A preliminary diagnosis system was developed based on an artificial neural network (ANN) to limit the searching space of the optimization algorithm and to set the initial parameters in the heart simulation model. The optimal heart-model parameters were obtained by minimizing the difference between the observed and model-generated body surface ECGs. The present computer simulation shows promising results indicating that the present approach produces a 100% success rate in localization of an area of acute MI in the left ventricle for cases studied. The present study suggests this approach merits further investigation, and may provide an important alternative to ECG inverse solutions
  • Keywords
    digital simulation; diseases; electrocardiography; inverse problems; medical image processing; neural nets; optimisation; physiological models; 3D heart-model based inverse imaging approach; ECG inverse solutions; artificial neural network; electrodiagnostics; myocardial infarction; noninvasive localization; optimal heart-model parameters; optimization algorithm searching space; preliminary diagnosis system; Artificial neural networks; Cardiac disease; Computational modeling; Computer simulation; Electrocardiography; Heart; Inverse problems; Myocardium; Pathology; Surface reconstruction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual International Conference of the IEEE
  • Conference_Location
    Chicago, IL
  • ISSN
    1094-687X
  • Print_ISBN
    0-7803-6465-1
  • Type

    conf

  • DOI
    10.1109/IEMBS.2000.897862
  • Filename
    897862