Document Type

Article

Publication Date

2024

DOI

10.1007/s00366-024-02023-w

Publication Title

Engineering with Computers

Volume

Article in Press

Pages

27 pp.

Abstract

Converting a three-dimensional medical image into a 3D mesh that satisfies both the quality and fidelity constraints of predictive simulations and image-guided surgical procedures remains a critical problem. Presented is an image-to-mesh conversion method called CBC3D. It first discretizes a segmented image by generating an adaptive Body-Centered Cubic mesh of high-quality elements. Next, the tetrahedral mesh is converted into a mixed element mesh of tetrahedra, pentahedra, and hexahedra to decrease element count while maintaining quality. Finally, the mesh surfaces are deformed to their corresponding physical image boundaries, improving the mesh’s fidelity. The deformation scheme builds upon the ITK open-source library and is based on the concept of energy minimization, relying on a multi-material point-based registration. It uses non-connectivity patterns to implicitly control the number of extracted feature points needed for the registration and, thus, adjusts the trade-off between the achieved mesh fidelity and the deformation speed. We compare CBC3D with four widely used and state-of-the-art homegrown image-to-mesh conversion methods from industry and academia. Results indicate that the CBC3D meshes: (1) achieve high fidelity, (2) keep the element count reasonably low, and (3) exhibit good element quality.

Rights

© 2024 The Authors.

This article is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original authors and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

Data Availability

Article states: "Not applicable for this work."

Original Publication Citation

Drakopoulos, F., Liu, Y., Garner, K., & Chrisochoides, N. (2024). Image-to-mesh conversion method for multi-tissue medical image computing simulations. Engineering with Computers. Advance online publication. https://doi.org/10.1007/s00366-024-02023-w

ORCID

0000-0003-3088-0187 (Chrisochoides)

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