A Novel Robust Tube Detection Filter for 3D Centerline Extraction

Centerline extraction of tubular structures such as blood vessels and airways in 3D volume data is of vital interest for applications involving registration, segmentation and surgical planing. In this paper, we propose a robust method for 3D centerline extraction of tubular structures. The method is based on a novel multiscale medialness function and additionally provides an accurate estimate of tubular radius. In contrast to other approaches, the method does not need any user selected thresholds and provides a high degree of robustness. For comparison and performance evaluation, we are using both synthetic images from a public database and a liver CT data set. Results show the advantages of the proposed method compared with the methods of Frangi et al. and Krissian et al.