Improved marching cubes using novel adjacent lookup table and random sampling for medical object-specific 3D visualization

The marching cubes (MC) algorithm is a widely used routine to extract isosurfaces from volumetric data set. This method suffers from the exhaustive accessing cubes sequentially and the failure of directly separating the isosurfaces. To address this, an improved MC algorithm called AlutMC is proposed to track connected surfaces by combining a new adjacent lookup table and random sampling technique. AlutMC has a natural ability to separate the isosurfaces related to different components, which can efficiently segment 3D objects without extra expenditure and helpful for visualizing medical objects. Experimental results on three test data sets show the computational efficiency in identifying isosurfaces. Additionally, it is simple and efficient, not requiring complex data structure, and can be used as is into the MC and its improvements because it is quite cost-effective and self-contained.