Uncertainty Visualization In Forward And Inverse Cardiac Models

Uncertainty Visualization In Forward And Inverse Cardiac Models
Brett M Burton, Burak Erem, Kristin Potter, Paul Rosen, Chris R Johnson, Dana H Brooks, and Rob S Macleod
IEEE Computing in Cardiology (CinC), 2013

Abstract

Quantification and visualization of uncertainty in cardiac forward and inverse problems with complex geometries is subject to various challenges. Specific to visualization is the observation that occlusion and clutter obscure important regions of interest, making visual assessment difficult. In order to overcome these limitations in uncertainty visualization, we have developed and implemented a collection of novel approaches. To highlight the utility of these techniques, we evaluated the uncertainty associated with two examples of modeling myocardial activity. In one case we studied cardiac potentials during the repolarization phase as a function of variability in tissue conductivities of the ischemic heart (forward case). In a second case, we evaluated uncertainty in reconstructed activation times on the epicardium resulting from variation in the control parameter of Tikhonov regularization (inverse case). To overcome difficulties associated with uncertainty visualization, we implemented linked-view windows and interactive animation to the two respective cases. Through dimensionality reduction and superimposed mean and standard deviation measures over time, we were able to display key features in large ensembles of data and highlight regions of interest where elevated uncertainties exist.

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Citation

Brett M Burton, Burak Erem, Kristin Potter, Paul Rosen, Chris R Johnson, Dana H Brooks, and Rob S Macleod. Uncertainty Visualization In Forward And Inverse Cardiac Models. IEEE Computing in Cardiology (CinC), 2013.

Bibtex


@inproceedings{burton2013uncertainty,
  title = {Uncertainty Visualization in Forward and Inverse Cardiac Models},
  author = {Burton, Brett M and Erem, Burak and Potter, Kristin and Rosen, Paul and
    Johnson, Chris R and Brooks, Dana H and Macleod, Rob S},
  booktitle = {IEEE Computing in Cardiology (CinC)},
  pages = {57--60},
  year = {2013},
  abstract = {Quantification and visualization of uncertainty in cardiac forward and
    inverse problems with complex geometries is subject to various challenges. Specific to
    visualization is the observation that occlusion and clutter obscure important regions of
    interest, making visual assessment difficult. In order to overcome these limitations in
    uncertainty visualization, we have developed and implemented a collection of novel
    approaches. To highlight the utility of these techniques, we evaluated the uncertainty
    associated with two examples of modeling myocardial activity. In one case we studied
    cardiac potentials during the repolarization phase as a function of variability in
    tissue conductivities of the ischemic heart (forward case). In a second case, we
    evaluated uncertainty in reconstructed activation times on the epicardium resulting from
    variation in the control parameter of Tikhonov regularization (inverse case). To
    overcome difficulties associated with uncertainty visualization, we implemented
    linked-view windows and interactive animation to the two respective cases. Through
    dimensionality reduction and superimposed mean and standard deviation measures over
    time, we were able to display key features in large ensembles of data and highlight
    regions of interest where elevated uncertainties exist.}
}