Two-stage Semi-automatic Organ Segmentation Framework using Radial Basis Functions and Level Sets
Andreas Wimmer, Grzegorz Soza, Joachim Hornegger · 2007
Abstract. The automatic segmentation of complex anatomical structures often fails due to low-contrast or missing edges, pathologic alterations, or high noise. As an alternative, we propose a novel two-stage semi-automatic algorithm that is able to segment complex structures like the liver shape with moderate user interaction. The first stage of our algorithm is the manual delineation of cross-sections of the anatomical structure in 2-D multi-planar reconstruction views. From this set of contours, an initial 3-D surface is reconstructed using radial basis functions. In a second step, the surface is evolved using a level set algorithm incorporating a new combination of both image information and shape information, the latter being derived from the initial contours. The algorithm has been evaluated for 10 Computed Tomography scans of the liver and has shown promising results. 1