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Tetrahedral Image-To-Mesh Conversion Software for Anatomic Modeling of Arteriovenous Malformations

Drakopoulos, Fotis, Ricardo Ortiz, Andinet Enquobahrie, Deanna Sasaki-Adams, Nikos Chrisochoides

24th International Meshing Roundtable, Elsevier Ltd., October 12-14 2015

IMR
PROCEEDINGS

24th International Meshing Roundtable
Austin, TX
October 12-14,2014

CRTC Lab, Department of Computer Science, Old Dominion University, Norfolk, VA 23529, USA
Kitware, Inc., Carrboro, NC, 27510, USA
Department of Neurosurgery, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
Email: nikos@cs.odu.edu

Abstract
We describe a new implementation of an adaptive multi-tissue tetrahedral mesh generator targeting anatomic modeling of Arteriovenous Malformation (AVM) for surgical simulations. Our method, initially constructs an adaptive Body-Centered Cubic (BCC) mesh of high quality elements. Then, it deforms the mesh surfaces to their corresponding physical image boundaries, hence, improving the mesh fidelity and smoothness. Our deformation scheme, which builds upon the ITK toolkit, is based on the concept of energy minimization, and relies on a multi-material point-based registration. It uses non-connectivity patterns to implicitly control the number of the extracted feature points needed for the registration, and thus, adjusts the trade-off between the achieved mesh fidelity and the deformation speed. While many medical imaging applications require robust mesh generation, there are few codes available to the public. We compare our implementation with two similar open-source image-to-mesh conversion codes: (1) Cleaver from US, and (2) CGAL from EU. Our evaluation is based on five isotropic/anisotropic segmented images, and relies on metrics like geometric & topologic fidelity, mesh quality, gradation and smoothness. The implementation we describe is opensource and it will be available within: (i) the 3D Slicer package for visualization and image analysis from Harvard Medical School, and (ii) an interactive simulator for neurosurgical procedures involving vasculature using SOFA, a framework for real-time medical simulation developed by INRIA.

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