Segmentation of 3D Tubular Tree Structures in Medical Images ...

58 Chapter 3. Grouping and Linkage into Connected Networks
(a) Volume rendering
of dataset.
(b) GVF-based
grouping and linkage
(Section 3.3).
(c) Structure based
grouping and linkage
(Section 3.2).
(d) Mutliscale tube
detection and simple
linkage.
(e) Hassouna’s skeletonization
approach.
(f) Bouix’s skeletonization
approach.
(g) Palagyi’s skeletonization
approach.
Figure 3.5: Curve skeletons of an airway tree. Green: Result of GVF-based grouping and
linkage (Section 3.3). Red: Other approaches.
directly from the gray value image. The skeletonization approaches are that of Hassouna
et al. [53–55], Bouix et al. [15], and Palagyi et al. [110]. Hassouna’s approach also
uses the GVF similarly to our approach; the other two methods were specifically developed
for tubular objects. As an alternative method that tries to extract centerlines directly from
gray value images we decided to use a combination of the methods of Krissian et al. [70]
(for a bottom-up detection of tubular structures) and Bullitt et al. [18] (for grouping the
single tubular objects into tree structures and an extraction of the complete CS). For all
approaches the authors default parameters were used. For our grouping/linkage meth-