A Generalized Marching Cubes Algorithm Based On Non-Binary Classifications

We present a new technique for generating surface meshes from a uniform set of discrete samples. Our method extends the well-known marching cubes algorithm used for computing polygonal isosurfaces. While in marching cubes each vertex of a cubic grid cell is binary classified as lying above or below an isosurface, in our approach an arbitrary number of vertex classes can be specified. Consequently the resulting surfaces consist of patches separating volumes of two different classes each. Similar to the marching cubes algorithm all grid cells are traversed and classified according to the number of different vertex classes involved and their arrangement. The solution for each configuration is computed on base of a model that assigns probabilities to the vertices and interpolates them. We introduce an automatic method to find a triangulation which approximates the boundary surfaces implicitly given by our model in a topological correct way. Look-up tables guarantee a high performance of the algorithm. In medical applications our method can be used to extract surfaces from a 3D segmentation of tomographic images into multiple tissue types. The resulting surfaces are well suited for subsequent volumetric mesh generation, which is needed for simulation as well as visualization tasks. The proposed algorithm provides a robust and unique solution, avoiding ambiguities occuring in other methods. The method is of great significance in modeling and animation too, where it can be used for polygonalization of non-manifold implicit surfaces.