Locally Adaptive Marching Cubes through Iso-Value Variation

Abstract

We present a locally adaptive marching cubes algorithm. It is a modification of the marching cubes algorithm where instead of a global iso-value each grid point has its own iso-value. This defines an iso-value field, which modifies the case identification process in the algorithm. The marching cubes algorithm uses linear interpolation to compute intersections of the surface with the cell edges. Our modification computes the intersection of two general line segments, because there is no longer a constant iso-value at each cube vertex. An iso-value field enables the algorithm to correct biases within the dataset like low frequency noise, contrast drifts, local density variations, and other artefacts introduced by the measurement process. It can also be used for blending between different isosurfaces (e.g., skin, veins, and bone in a medical dataset).