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

116 Chapter 7. Airway Tree Segmentation
sented methods on the 20 testing datasets and for comparison results achieved with other
methods. The quantitative measures were provided by the “Extraction of Airways from CT
2009 (EXACT09)” database and are available online at http://image.diku.dk/exact.
7.3.1 Results of Proposed Methods
Tables 7.1 and 7.2 summarize the evaluation results for the 20 testing datasets of both
methods. For the GVF based method (Table 7.1), on average 63.0% of airway branches
were detected with an average detected tree length of 58.4%. The mean leakage count
was 5.0, and the mean false positive rate was 1.44% (median: 0.61%). For the airway tree
reconstruction method (Table 7.2), on average, 57.9% of airway branches were detected
with an average detected tree length of 55.2%. The mean leakage count was 6.5, and the
mean false positive rate was 2.44% (median: 1.41%).
7.3.2 Comparison to Other Methods
A larger set of other methods [13, 35, 36, 38, 57, 76, 87, 100, 112, 147, 154, 158, 160] has
been evaluated on the “Extraction of Airways from CT 2009 (EXACT09)” database. The
results achieved with these methods are summarized in Table 7.3 and Fig. 7.5. We refrain
from detailed discussions of all other methods referring for this purpose to the work of
Lo et al. [88] and only provide a short comparison of our proposed method with the other
methods.
Most methods for airway tree segmentation are fully automated methods, or they are
semi-automated methods that require only minimal user interaction such as selecting initial
seed points inside the trachea or adaption of parameters. An exception is the method of
Tschirren et al. [147] that is part of a clinical product. Their software allows for extensive
editing of an initial segmentation result. What all other methods have in common, is that
they use region-growing or wave propagation approaches for extraction of the airway trees.
The methods evolve starting from a seed inside trachea and recursively merge potential
airway regions, usually combined with a method for leakage prevention.
A large variation between the performance of the different methods can be observed as
well as a general trade-off between extraction capability and leakage as shown in Fig. 7.5.
Methods with higher branch count also show a higher leakage volume and vice versa. The
better methods show an ability to extract about 55-60% of the airway tree with a false
positive rate of below 5%. The method with the highest extraction capability also allows
extraction of only about 75%. However, to the cost of a false positive rate of more than