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Texture Mapping by Isometric Spherical Embedding for the Visualization and Assessment of Regional Myocardial Function

  • Yechiel Lamash
  • Anath Fischer
  • Jonathan Lessick
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7945)

Abstract

In the current study we show how texture mapping to the surface of the heart’s left ventricle(LV) can be used to demonstrate the ventricle’s complex kinematics and highlight impaired regions. The method uses isometric spherical embedding to map a uniform and oriented texture into a reference phase of the LV’s mesh. The texture, attached to the deformed mesh, deforms with it and allows the visualization of rotation, strain and torsion in the circumferential and longitudinal coordinates. Such visualization demonstrates the absolute and relative values of these kinematic parameters and aids in the assessment of regional myocardial function.

Keywords

Left Ventricle Principal Strain Geodesic Distance Texture Mapping Regional Myocardial Function 
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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References

  1. 1.
    Borg, I., Lingoes, J.C.: A model and algorithm for multidimensional scaling with external constraints on the distances. Psychometrika 45(1), 25–38 (1980)zbMATHCrossRefGoogle Scholar
  2. 2.
    Bronstein, A.M., Bronstein, M.M., Kimmel, R.: Isometric embedding of facial surfaces into formula_image. In: Kimmel, R., Sochen, N.A., Weickert, J. (eds.) Scale-Space 2005. LNCS, vol. 3459, pp. 622–631. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  3. 3.
    Bronstein, A.M., Bronstein, M.M., Kimmel, R.: Numerical geometry of non-rigid shapes. Springer (2008)Google Scholar
  4. 4.
    De Leeuw, J.: Multidimensional scaling (2011)Google Scholar
  5. 5.
    Elad, A., Kimmel, R.: Spherical flattening of the cortex surface. In: Geometric Methods in Bio-medical Image Processing, pp. 77–89 (2002)Google Scholar
  6. 6.
    Gotsman, C., Gu, X., Sheffer, A.: Fundamentals of spherical parameterization for 3d meshes. ACM Transactions on Graphics (TOG) 22, 358–363 (2003)CrossRefGoogle Scholar
  7. 7.
    Kimmel, R., Sethian, J.A.: Computing geodesic paths on manifolds. Proceedings of the National Academy of Sciences 95(15), 8431–8435 (1998)MathSciNetzbMATHCrossRefGoogle Scholar
  8. 8.
    Morrison, A., Ross, G., Chalmers, M.: Fast multidimensional scaling through sampling, springs and interpolation. Information Visualization 2(1), 68–77 (2003)CrossRefGoogle Scholar
  9. 9.
    Praun, E., Hoppe, H.: Spherical parametrization and remeshing. ACM Transactions on Graphics (TOG) 22(3), 340–349 (2003)CrossRefGoogle Scholar
  10. 10.
    Saba, S., Yavneh, I., Gotsman, C., Sheffer, A.: Practical spherical embedding of manifold triangle meshes. In: 2005 International Conference on Shape Modeling and Applications, pp. 256–265. IEEE (2005)Google Scholar
  11. 11.
    Sheffer, A., Praun, E., Rose, K.: Mesh parameterization methods and their applications. Foundations and Trends® in Computer Graphics and Vision 2(2), 105–171 (2006)CrossRefGoogle Scholar
  12. 12.
    Stanton, T., Marwick, T.H.: Assessment of subendocardial structure and function. JACC: Cardiovascular Imaging 33(8), 867–875 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yechiel Lamash
    • 1
  • Anath Fischer
    • 1
  • Jonathan Lessick
    • 2
  1. 1.Technion—Israel Institute of TechnologyHaifaIsrael
  2. 2.Rambam - Health Care CampusHaifaIsrael

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