A new automatic skeletonization algorithm for 3D vascular volumes

Extraction of the skeleton of vascular structures is an important procedure for computer aided analysis of vascular data. A new automatic skeletonization algorithm for 3D vascular volumes is proposed. Two types of distance maps and clusters, a set of connected points with the same property are used to represent the vascular structure. Using clusters representation, branch information can be retrieved efficiently. In each identified branch, preliminary points, defined as skeleton nodes, are derived hierarchically which are later interpolated to generate the skeleton. The algorithm was tested on MR angiography arterial and venous 3D vascular volumes. The extracted skeletons were reliable representation of the vascular structure. Compared to other 3D distance-based skeletonization algorithms, the new approach yields a more centered skeleton without complex post-processing. The skeleton is also insensitive to boundary complexity and can be easily modified by the user.