Image to Mesh Conversion


The goal of this project is to create fast and robust software for generating tetrahedral meshes from (segmented) image data. This task challenges traditional approaches to mesh generation, as no surface information is available as such.

We explore two conceptual approaches to mesh generation: (1) segmentation of the structure of interest with subseqent surface recovery and applying state of the art methods to tesselate the volume, and (2) generate the volume mesh directly from the segmentation (or even unprocessed image).


Currently, there are two main driving applications for this project:image-guided neurosurgery(IGNS), and large scale simulation of arterial blood flow.

The mesh generator we developed facilitates construction of biomechanical model of brain for intraoperative non-rigid registration of preoperative MRI. The mesher works directly with the segmented image data, it is fast and generates meshes of quality comparable with the state of the art counterparts, which require object surface to be recovered first.

Up until recently, our implementation was enabling intraoperative registration studies at Brigham and Women's Hospital, Boston.

Brain mesh surface Graded mesh cut
Vol mesh with bg Surface and bg

Tetrahedral mesh is essential for construction of biomechanical model of brain deformation.

Our collaboration project targeting construction of tetrahedral meshes for arterial blood flow simulations is currently in the early stages of development. Our initial objectives of the study in this area is the assessment of available approaches and evaluation of application-defined requirements.

Artery hires Bifurcations

Surface of the tetrahedral mesh recostructed from segmented artery volume;
color-coded is volume element quality as measured by aspect ratio.


The following software is used in this project.

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