Three-dimensional Radial Active Contour Model: A 3-D to 1-D Image Segmentation Technique

In this paper we present a new technique of 3D volume segmentation to be applied in general 3D shapes. This technique, called Three-dimensional Radial Active Contour Model (3D Radial Snakes), generalize the concept of Active Rays and use the idea of rays coming from a central point inside an object of interest to be segmented. This rays lies among a 3D space and are represented by two angles and it's length. The idea of this model is to achieve the edge of the object of interest by the analysis of the information only on the ray (1D). We perform tests in synthetic 3D shapes varying the number of rays and computing the mean distance from the original shape and calculating how similar the shapes are. We calculate the processing time by segmentation cycles and compare against 3D Region Growing technique. The obtained results from synthetic volumes show that this method can be applied in image segmentation with good accuracy in a very fast way.