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

Chapter 4
Tube Segmentation
Contents
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
4.2 Inverse Gradient Vector Flow Tracking . . . . . . . . . . . . . . 66
4.3 Graph Cut Based Tree Segmentation . . . . . . . . . . . . . . . 68
4.4 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
4.5 Discussion and Conclusion . . . . . . . . . . . . . . . . . . . . . . 74
4.1 Introduction
In the last two chapters, we presented methods for the extraction of structural representations
of tubular tree structures. The derived representations consist of centerlines/skeletons
usually associated with a radius and tangent direction estimate for each
centerline point. Such a representation can be seen as a segmentation result [18, 68],
however, this information does not accurately represent the actual surfaces of the tubular
objects. The known structures could be utilized as a good initialization for a segmentation
method (e.g., levelsets) to obtain more accurate segmentations. However, most segmentation
methods do not necessarily preserve the topology of the already known tree structure
as the methods may still show leakage (additional branches in the tree) or holes/gaps in
the segmentation results (unconnected branches in the tree). In this chapter, we are concerned
with methods to obtain accurate segmentations related to already known tubular
structures that make use of the already known information in such a way that the topology
is preserved.
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