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Motion Estimation with Finite-Element Biomechanical Models and Tracking Constraints from Tagged MRI

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Book cover Computational Biomechanics for Medicine

Abstract

Noninvasive measurements of tissue deformation provide biomechanical insights of an organ, which can be used as clinical functional biomarkers or experimental data for validating computational simulations. However, acquisition of 3D displacement information is susceptible to experimental inconsistency and limited scan time. In this research, we describe the process of tracking tagged magnetic resonance imaging (MRI) as enforcing harmonic phase conservation in finite-element (FE) models. This concept is demonstrated as a tool for motion estimation in an experimental brain phantom, and images from the human heart and tongue. Our results demonstrate that the new methodology offers robustness to edge and large-displacement artifacts, and that it can be seamlessly coupled with numerical simulations for estimating fiber stretch in residually stressed tissue, or for inverse identification of muscle activation.

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Acknowledgments

This research was funded by NIH Grant R01-NS055951, supplement PA12-149, and support by the Center for Neuroscience and Regenerative Medicine.

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Authors and Affiliations

  1. Electrical and Computer Engineering Department, Johns Hopkins University, Baltimore, MD, USA

    Arnold D. Gomez & Jerry L. Prince

  2. Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA

    Fangxu Xing

  3. Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation, Bethesda, MD, USA

    Deva Chan & Dzung L. Pham

  4. Mechanical Engineering Department, Washington University in St. Louis, St. Louis, MO, USA

    Philip Bayly

Authors
  1. Arnold D. Gomez
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  2. Fangxu Xing
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  3. Deva Chan
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  4. Dzung L. Pham
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  5. Philip Bayly
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  6. Jerry L. Prince
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Corresponding author

Correspondence to Arnold D. Gomez .

Editor information

Editors and Affiliations

  1. Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Perth, West Australia, Australia

    Adam Wittek

  2. Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Perth, West Australia, Australia

    Grand Joldes

  3. Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand

    Poul M.F. Nielsen

  4. School of Mechanical and Chemical Engineering, The University of Western Australia, Perth, West Australia, Australia

    Barry J. Doyle

  5. Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Perth, West Australia, Australia

    Karol Miller

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Gomez, A.D., Xing, F., Chan, D., Pham, D.L., Bayly, P., Prince, J.L. (2017). Motion Estimation with Finite-Element Biomechanical Models and Tracking Constraints from Tagged MRI. In: Wittek, A., Joldes, G., Nielsen, P., Doyle, B., Miller, K. (eds) Computational Biomechanics for Medicine. Springer, Cham. https://doi.org/10.1007/978-3-319-54481-6_7

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  • DOI: https://doi.org/10.1007/978-3-319-54481-6_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54480-9

  • Online ISBN: 978-3-319-54481-6

  • eBook Packages: EngineeringEngineering (R0)

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