Tamed snake: A particle system for robust semi-automatic segmentation

Abstract

Semi-automatic segmentation approaches tend to overlook the problems caused by missing or incomplete image information. In such situations, powerful control mechanisms and intuitive modelling metaphors should be provided in order to make the methods practically applicable. Taking this problem into account, the usage of subdivision curves in combination with the simulation of edge attracted mass points is proposed as a novel way towards a more robust interactive segmentation methodology. Subdivision curves provide a hierarchical and smooth representation of a shape which can be modified on coarse and on fine scales as well. Furthermore, local adaptive subdivision gives the required flexibility when dealing with a discrete curve representation. In order to incorporate image information, the control vertices of a curve are considered mass points, attracted by edges in the local neighbourhood of the image. This so-called Tamed Snake framework is illustrated by means of the segmentation of two medical data sets and the results are compared with those achieved by traditional Snakes.