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

Chapter 8
Conclusion and Outlook
Contents
8.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
8.2 Directions for Future Work . . . . . . . . . . . . . . . . . . . . . 128
8.1 Conclusion
In this work we were dealing with the segmentation of 3D tubular tree structures in medical
images. In the introduction, we outlined the general requirements and objectives
for different applications in this field, emphasizing the importance of the structural correctness,
and reviewed related work on vessel/airway segmentation. Based on that we
presented a general approach for segmentation of branched tubular networks (Section 1.2)
that puts a strong focus on the structural correctness of the segmentation results. The
approach consists of a tube extraction step, a grouping and linkage step, and the actual
tube segmentation step.
We developed and investigated methods for each of these processing steps, leading
to a set of flexible methods that can be utilized in various applications. In particular,
in Chapter 2 we developed a novel approach for detection of tubular objects based on
the GVF that addresses limitations of these typically used Gaussian scale space based
methods and compared it to promising TDFs known from the literature. In Chapter 3
we proposed two methods for grouping and linkage of unconnected tubular structures
into tubular tree structures, one enabling an extraction of high quality centerlines in that
deviate significantly from the typical tube shape, while the other one allows for a separation
of interwoven tubular tree structures as well as handling of various kinds of disturbances.
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