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Regularization in Cardiac Source Imaging

  • Tuomas Lunttila
  • Jukka Nenonen
  • Erkki Somersalo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2674)

Abstract

Estimation of bioelectric currents in the heart involves the solution of an ill-posed inverse problem in electro- and magnetocardiography. The problem becomes linear in respect to current magnitudes when the equivalent sources are constrained into a pre-determined grid of reconstruction points. Still, a proper regularization is required to obtain physiologically meaningful results. This paper discusses the application of deterministic methods (such as Tikhonov or Wiener regularization) and statistical inversion. The deterministic methods require determination of an optimal regularization parameter, while the statistical inversion relies on application of a prior for the source distribution. Comparison of selected regularization methods is performed with simulated magnetocardiographic data.

Keywords

Inverse Problem Electrical Impedance Tomography Tikhonov Regularization Markov Chain Monte Carlo Method Hastings Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Tuomas Lunttila
    • 1
  • Jukka Nenonen
    • 1
    • 2
  • Erkki Somersalo
    • 3
  1. 1.Laboratory of Biomedical EngineeringHelsinki University of TechnologyEspooFinland
  2. 2.BioMag LaboratoryHelsinki University Central HospitalHelsinkiFinland
  3. 3.Institute of MathematicsHelsinki University of TechnologyEspooFinland

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