Computational cardiac anatomy using MRI

Authors

  • Mirza Faisal Beg,

    1. Center for Imaging Science, The Whitaker Biomedical Engineering Institute, Johns Hopkins University School of Medicine and Whiting School of Engineering, Baltimore, Maryland
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    • M.F. Beg and P.A. Helm contributed equally to this work

  • Patrick A. Helm,

    1. Center for Cardiovascular Bioinformatics & Modeling, The Whitaker Biomedical Engineering Institute, Johns Hopkins University School of Medicine and Whiting School of Engineering, Baltimore, Maryland
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    • M.F. Beg and P.A. Helm contributed equally to this work

  • Elliot McVeigh,

    1. Laboratory of Cardiac Energetics, National Heart Lung Blood Institute, National Institutes of Health, Bethesda, Maryland
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  • Michael I. Miller,

    1. Center for Imaging Science, The Whitaker Biomedical Engineering Institute, Johns Hopkins University School of Medicine and Whiting School of Engineering, Baltimore, Maryland
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  • Raimond L. Winslow

    Corresponding author
    1. Center for Cardiovascular Bioinformatics & Modeling, The Whitaker Biomedical Engineering Institute, Johns Hopkins University School of Medicine and Whiting School of Engineering, Baltimore, Maryland
    • Rm. 201B Clark Hall, Johns Hopkins University, 3400 N. Charles St., Baltimore MD 21218
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  • This article is a US Government work and, as such, is in the public domain in the United States of America.

Abstract

Ventricular geometry and fiber orientation may undergo global or local remodeling in cardiac disease. However, there are as yet no mathematical and computational methods for quantifying variation of geometry and fiber orientation or the nature of their remodeling in disease. Toward this goal, a landmark and image intensity-based large deformation diffeomorphic metric mapping (LDDMM) method to transform heart geometry into common coordinates for quantification of shape and form was developed. Two automated landmark placement methods for modeling tissue deformations expected in different cardiac pathologies are presented. The transformations, computed using the combined use of landmarks and image intensities, yields high-registration accuracy of heart anatomies even in the presence of significant variation of cardiac shape and form. Once heart anatomies have been registered, properties of tissue geometry and cardiac fiber orientation in corresponding regions of different hearts may be quantified. Magn Reson Med 52:1167–1174, 2004. Published 2004 Wiley-Liss, Inc.

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