Robust and Fully Automatic Tetrahedral Mesh-Generation for Multi-Domain High-Resolution Computational Anatomical Models

Semester and Master's Work at the IT'IS Foundation - Robust and Fully Automatic Tetrahedral Mesh-Generation for Multi-Domain High-Resolution Computational Anatomical Models


Automatic tetrahedral mesh generation for 3D multi-domains, a fundamental step in the construction of realistic models for finite element method (FEM) analysis, has received a significant amount of attention in recent years (see [1]).

In particular, automatic mesh generation of realistic biomechanical models is a challenging task due to the very diverse geometric scales present in the human body and the inherently complex topology of human tissues ([2]). The conventional workflow involves a segmentation step needed to delineate the anatomy followed by a meshing step., which is often a cumbersome and time-consuming process that constitutes a major bottleneck that side-rails automation of the modeling-simulation pipeline.

The aim of this project is to develop a robust and fully automated octree-based mesh-generation algorithm capable of producing high-quality tetrahedral meshes from segmented images for realistic cases ([3]). The main focus will be on accurate reconstruction of the interfaces between different body-tissues [4]. The extent of the project will be defined and finalized according to the interests and background of the student.

The student should have good/intermediate programming skills (C++) and will be provided with a main algorithmic framework (Sim4Life).

The workflow will include:

  • a survey of the approaches reported in recent literature
  • development of the mesh-generation framework in C++
  • investigation of efficient computational architectures (e.g., GPU processing)
  • assessment of the quality and robustness of the mesh generation scheme in realistic scenarios

Please contact Dr. Alessandro Alaia for more information and further details.

  1. Zhang Y. ed. “Image-Based Geometric Modeling and Mesh Generation”, Lecture Notes in Computational Vision and Biomechanics Series, Springer Netherlands, 2013, DOI: 10.1007/978-94-007-4255-0.
  2. Zhang Y. ed. “Geometric Modeling and Mesh Generation from Scanned Images”, Chapman & Hall/CRC Mathematical and Computational Imaging Sciences Series, vol. 6, CRC Press, Taylor & Francis Group 2016.
  3. Liang, X. and Zhang, Y. “An Octree-Based Dual Contouring Method for Triangular and Tetrahedral Mesh Generation with Guaranteed Angle Range”. Engineering with Computers, 2014, 30: 211–222.
  4. Zhang Y., Hughes T. J. R., and Bajaj C. L.  “An Automatic 3D Mesh Generation Method for Domains with Multiple Materials”. Computer Methods in Applied Mechanics and Engineering, 2010, 199: 405–415.

Dr. Alessandro AlaiaDr. Bryn Lloyd

Type of Work:



Niels Kuster

Please send applications to Mimi Sun at