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

IT'IS Foundation -
Zürich, ZH

Jetzt bewerben

Details zur Stelle

Qualifikationen

Vollständige Stellenbeschreibung

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. Bryn Lloyd for more information and further details.

References

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.

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.

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.

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.

Supervisors:

Dr. Bryn Lloyd

Type of Work:

Computation

Professor:

Niels Kuster

Please send applications to Yvonne Maeder at [email protected]

Jetzt bewerben

Erweiterte Suche

computer vision Jobs in oberrohrdorf ag

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

AI Engineer / Consultant

VLA Researcher (m/f/d)

Lead Database Architect (80-100%)

Application Manager

Principal Data Architect

Principal Product Manager, Robotics

Customer Success Technical Advisor

Senior Software Engineer, Formal Verification Engineer

Senior Research Scientist, Deep Learning

AI Research Engineer (Kernel & Inference Optimization)

Technical Customer Success Manager, Switzerland

Technical Product Manager QVAC - 100% remote

Customer Solution Engineer (Zurich)

Senior Staff Software Engineer - Delta

Technical Consultant (m/w/d)

Regional Head IT Business Engagement - Europe

Platform Owner 100% (f/m/d)

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Reinforcement Learning Expert - Humanoid (Mensch)

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