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Computational Cardiovascular Mechanics pp 103–119Cite as

Vascular Geometry Reconstruction and Grid Generation

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Abstract

The geometry of vascular system is an important determinant of blood flow in health and disease. There is a strong geometric component to atherosclerosis in coronary heart disease since lesions are preferentially located at bifurcation points and regions of high curvature. The influence of these local structures on recirculation and deleterious shear stresses and their role in plaque development is widely accepted. Over time, researchers have turned to MR, CT, or biplane images of vascular trees to faithfully capture these features in the flow simulations. Historically, this has taken the form of labor-intensive manual reconstructions from morphometric measurements based on the centerline, whereby small idealized subsets of vascular trees are developed into computational grids. With improved imaging, image processing, and geometric reconstruction algorithms, researchers have begun to develop geometrically accurate computational models directly from the medical images. This chapter provides an overview of contemporary methods for image processing, centerline detection, boundary condition definition, and grid generation of both clinical and research images of cardiovascular structures.

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Acknowledgments

This research was supported in part by Wright State University; the Ohio Board of Regents; the National Heart and Blood Institute HL055554-11, HL-084529, and HL073598; the National Institute of Environmental Health Sciences P01ES011617; and by the National Science Foundation DMS-0809285.

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Wright State University, Dayton, OH, USA

    Thomas Wischgoll

  2. Pacific Northwest National Laboratory, Richland, WA, USA

    Daniel R. Einstein & Andrew P. Kuprat

  3. Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA

    Xiangmin Jiao

  4. Weldon School of Biomedical Engineering, Purdue University, Indianapolis, IN, USA

    Ghassan S. Kassab

  5. Department of Biomedical Engineering, Indianapolis, IN, USA

    Ghassan S. Kassab

  6. Department of Surgery, Indianapolis, IN, USA

    Ghassan S. Kassab

  7. Department of Cellular and Integrative Physiology, Indianapolis, IN, USA

    Ghassan S. Kassab

  8. Indiana Center for Vascular Biology and Medicine, IUPUI, 46202, Indianapolis, IN, USA

    Ghassan S. Kassab

Authors
  1. Thomas Wischgoll
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  2. Daniel R. Einstein
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  3. Andrew P. Kuprat
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  4. Xiangmin Jiao
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  5. Ghassan S. Kassab
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Corresponding author

Correspondence to Thomas Wischgoll .

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Editors and Affiliations

  1. Veterans Affairs Medical Center, University of California, San Francisco, Clement St. 4150, San Francisco, 94121, U.S.A.

    Julius M. Guccione

  2. Purdue University Indianapolis, Indiana University, Barnhill Drive 635, Indianapolis, 46202, U.S.A.

    Ghassan S. Kassab

  3. Veterans Affairs Medical Center, University of California, San Francisco, Clement St. 4150, San Francisco, 94121, U.S.A.

    Mark B. Ratcliffe

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Wischgoll, T., Einstein, D.R., Kuprat, A.P., Jiao, X., Kassab, G.S. (2010). Vascular Geometry Reconstruction and Grid Generation. In: Guccione, J., Kassab, G., Ratcliffe, M. (eds) Computational Cardiovascular Mechanics. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-0730-1_7

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  • DOI: https://doi.org/10.1007/978-1-4419-0730-1_7

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  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-0729-5

  • Online ISBN: 978-1-4419-0730-1

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