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Automatically generated, anatomically accurate meshes for cardiac electrophysiology problems.

Anton J Prassl1, Ferdinand Kickinger, Helmut Ahammer

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Summary

A new method generates detailed, anatomically accurate unstructured mesh models of the heart from 3D images. This technique is ideal for advanced cardiac electrophysiology simulations and computational modeling.

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Area of Science:

  • Computational modeling and simulation
  • Biomedical imaging and image analysis
  • Cardiac electrophysiology

Background:

  • Advancements in imaging and computing enable detailed heart models.
  • Discretization of imaging data is crucial for modeling.
  • Unstructured grids are preferred for general heart models over structured grids.

Purpose of the Study:

  • To propose a novel image-based unstructured mesh generation technique for realistic heart models.
  • To create conformal, boundary-fitted, hexahedra-dominant meshes automatically.
  • To enable accurate cardiac electrophysiological simulations.

Main Methods:

  • Utilized the dual mesh of an octree applied to segmented 3D image stacks.
  • Developed a fully automatic algorithm requiring no interactivity.
  • Generated volume-preserving representations of complex geometries with smooth surfaces.

Main Results:

  • Produced conformal, boundary-fitted, hexahedra-dominant meshes.
  • Minimized element size variations within the myocardium.
  • Grew element size away from myocardial surfaces to reduce computational load.
  • Demonstrated numerical feasibility by solving monodomain and bidomain equations on generated grids.

Conclusions:

  • The proposed method offers an automatic and accurate approach for generating unstructured meshes from cardiac image data.
  • The generated meshes are suitable for high-fidelity cardiac electrophysiological simulations.
  • This technique facilitates the creation of generally applicable and computationally efficient heart models.