CSDL Home IEEE Transactions on Visualization & Computer Graphics 2008 vol.14 Issue No.01 - January/February

Subscribe

Issue No.01 - January/February (2008 vol.14)

pp: 160-172

ABSTRACT

In this paper we describe a novel 3-D subdivision strategy to extract the surface of binary image data. This iterative approach generates a series of surface meshes that capture different levels of detail of the underlying structure. At the highest level of detail, the resulting surface mesh generated by our approach uses only about 10% of the triangles in comparison to the marching cube algorithm (MC) even in settings were almost no image noise is present. Our approach also eliminates the so-called 'staircase effect' which voxel based algorithms like the MC are likely to show, particularly if non-uniformly sampled images are processed. Finally, we show how the presented algorithm can be parallelized by subdividing 3-D image space into rectilinear blocks of subimages. As the algorithm scales very well with an increasing number of processors in a multi-threaded setting, this approach is suited to process large image data sets of several gigabytes. Although the presented work is still computationally more expensive than simple voxel based algorithms, it produces fewer surface triangles while capturing the same level of detail, is more robust towards image noise and eliminates the above mentioned 'stair-case' effect in anisotropic settings. These properties make it particularly useful for biomedical applications, where these conditions are often encountered.

INDEX TERMS

isosurface extraction, adaptive mesh generation, Delaunay triangulation, parallel computing

CITATION

YingLiang Ma, "A Parallelized Surface Extraction Algorithm for Large Binary Image Data Sets Based on an Adaptive 3-D Delaunay Subdivision Strategy",

*IEEE Transactions on Visualization & Computer Graphics*, vol.14, no. 1, pp. 160-172, January/February 2008, doi:10.1109/TVCG.2007.1057REFERENCES

- [1] W.E. Lorensen and H.E. Cline, “Marching Cubes: A High Resolution 3D Surface Construction Algorithm,”
Proc. ACM SIGGRAPH '87, pp. 163-169, 1987.- [7] G.M. Nielson, “On Marching Cubes,”
IEEE Trans. Visualization and Computer Graphics, vol. 9, pp. 283-297, 2003.- [8] A. Lopes and K. Brodlie, “Improving the Robustness and Accuracy of the Marching Cubes Algorithm for Isosurfacing,”
IEEE Trans. Visualization and Computer Graphics, vol. 9, pp. 16-29, 2002.- [10] S.F.F. Gibson, “Constrained Elastic Surface Nets: Generating Smooth Surfaces from Binary Segmented Data,”
Lecture Notes in Computer Science, vol. 1496, pp. 888-898, 1998.- [11] G.M. Nielson, “Dual Marching Cubes,”
Proc. 15th IEEE Conf. Visualization (VIS '04), 2004.- [13] R. Shu, C. Zhou, and M.S. Kankanhalli, “Adaptive Marching Cubes,”
The Visual Computer, vol. 11, pp. 202-217, 1995.- [15] W.J. Schroeder, B. Geveci, and M. Malaterre, “Compatible Triangulations of Spatial Decompositions,”
Proc. 15th IEEE Conf. Visualization (VIS '04), 2004.- [18] R. Eils and K. Sätzler, “Shape Reconstruction from Volumetric Data,”
Handbook of Computer Vision and Applications, first ed., B. Jähne, H. Haußecker, and P. Geißler, eds., vol.2, pp. 791-815, Academic Press, 1999.- [19] R. Eils, E. Bertin, K. Saracoglu, B. Rinke, F. Parazza, E. Schröck, Y. Usson, M. Robert-Nicoud, J.M. Chassery, E.H.K. Stelzer, T. Cremer, and C. Cremer, “Application of Laser Confocal Microscopy and 3D-Voronoi Diagrams for Volume and Surface Estimates of Interphase Chromosomes,”
J. Microscopy, vol. 177, pp. 150-161, 1995.- [20] Z. Yaniv and K. Cleary, “Image-Guided Procedures: A Review,” technical report, Imaging Science and Information Systems, Georgetown Univ., 2006.
- [22] CGAL Web site, http:/www.cgal.org, 1997.
- [23] D.A. Berry,
Statistics: A Bayesian Perspective. Duxburry Press, 1996.- [25] VTK Web site, http:/www.vtk.org, 1993.
- [26] ImageJ Web site, http://rsb.info.nih.govij/, 1997.
- [28] S. Bischoff and L. Kobbelt, “Isosurface Reconstruction with Topology Control,”
Proc. 10th Pacific Conf. Computer Graphics and Applications (PG '02), pp. 246-255, 2002.- [29] S. Bischoff and L. Kobbelt, “Topologically Correct Extraction of the Cortical Surface of a Brain Using Level-Set Methods,” RWTH Aachen, 2004.
- [31] M. Garland and P.S. Heckbert, “Surface Simplification Using Quadric Error Metrics,”
Proc. ACM SIGGRAPH '97, pp. 209-216, 1997.- [33] J.D. Boissonnat and B. Geiger,
Three–Dimensional Reconstruction of Complex Shapes Based on the Delaunay Triangulation, INRIA Research Reports 1697, May 1992. |