## 5 Discussion  
In this paper, we have used several parameters to initialize and process our proposed system, as shown in Table 1. Some parameter values are meaningful, such as \(N\) and \(R\). The parameter \(N\) is number  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Case**} & \multirow{2}{*}{**Lung**} & \multicolumn{3}{c}{**Mean (\%)**} \\ \cline{3-5}  & & **Precision** & **Recall** & **F-measure** \\ \hline
1 & Left & 88.7 & 81.79 & 85.1 \\
2 & Left & 70.39 & 76.52 & 73.33 \\
3 & Left & 78.65 & 84.95 & 81.68 \\
4 & Left & 79.94 & 79.99 & 79.96 \\
5 & Left & 83.77 & 87.51 & 85.6 \\
6 & Left & 75.66 & 85.84 & 80.43 \\
7 & Left & 82.21 & 89.4 & 85.65 \\
8 & Left & 74.4 & 81.7 & 77.88 \\
9 & Left & 76.09 & 84.36 & 80.01 \\
10 & Left & 76.83 & 88.58 & 82.29 \\
11 & Left & 72.13 & 81.62 & 76.58 \\
12 & Left & 86.65 & 84.15 & 85.38 \\
13 & Left & 71.38 & 79.37 & 75.16 \\
14 & Left & 79.4 & 84.05 & 81.66 \\
15 & Left & 77.72 & 88.5 & 82.76 \\ \multicolumn{2}{c}{Average} & 78.26 & 83.89 & 80.9 \\ \hline \hline \end{tabular}
\end{table}
Table 2: The experimental results of precision, recall and F-measure by the proposed ACO method for 15 left lung cases.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Case**} & \multirow{2}{*}{**Lung**} & \multicolumn{3}{c}{**Mean (\%)**} \\ \cline{3-5}  & & **Precision** & **Recall** & **F-measure** \\ \hline
1 & Right & 80.32 & 85.73 & 82.94 \\
2 & Right & 75.75 & 87.11 & 81.03 \\
3 & Right & 78.46 & 83.  
of ants; we used 10 ants to track the candidate path through their pheromone in _PHM_ table (pheromote table) in each round. In our experiment, the result of \(N>10\) is similar to \(N=10\). Besides, if the number of ants (\(N\)) is too large, the system performance will be decreased. Therefore, we set parameter \(N\) is 10 in our study. Second, \(R\) is the number of path-tracking rounds. We can see the experimental results in Figures 8 and 9; the optimal path can be obtained in the fifth round. However, if \(R>5\), the results are the same as \(R=5\). Therefore, with consideration to performance, we set the parameter \(R\) is 5. The other parameters, \(p\), \(q\), \(a\) and \(\rho\) are probability parameters, \(p\) and \(q\) are used to control the path direction during ant moving, \(\alpha\) and \(\rho\) are used to enhance the pheromone in _PHM_ table by the global rules and local rules, respectively. These parameters, \(p\), \(q\), \(\alpha\) and \(\rho\), are expired values in our experiments.  
Besides, we have no comparison with other methods. The reason is most researches of lobe fissure were focused on the axial slices in CT. However, the imaging structure of axial view cannot display the whole information of lung lobe. Besides, the lobe fissure in axial slice is not a clear line; it may be an irregular region. The proposed ACO method is an ant-tracking algorithm. If the tracking path is not similar to a line or curve, we cannot define the start and end points to initialize our system. Hence, the proposed method cannot apply to an axial slice, and we only focus on sagittal view to obtain the lobe fissures on left lung and right lung, respectively. Through this proposed method, most of the lobe fissures can still be obtained and the metric values are also satisfied according to the results in Tables 2 and 3. Therefore, this performance of proposed method in this study can also be proved.