# Automatic Method for Bone Segmentation in Cone Beam Computed Tomography Data Set
## 3 Results  
The reliability of segmentations performed by surgeon was evaluated by calculating ICC values for preoperative and postoperative CBCT data sets (Table 1). The results show that in preoperative data ICC = 0.958 with 95% confidence interval [0.896... 0.983] and in postoperative data ICC = 0.931 with 95% confidence interval [0.836... 0.972]. Calculated values of ICC show that the level of surgeon reliability is sufficient [22]. (1) The mean RMS value of intersurface distance in preoperative cases was 0.559 mm and in postoperative--0.647 mm. Calculated RMS values of intersurface distance for all cases are presented by a boxplot in Figure 6.  
The interquartile range of boxplot is narrower for preoperative RMS values. The bigger distribution of RMS values is seen in postoperative cases. This could have been caused by a better quality of preoperative CBCT data sets. (2) The mean value of DSC was 0.921 in preoperative cases. In postoperative cases, the mean value of DSC was 0.911. Calculated DSC values are similar and are very high--more than 0.9. The results of DSC in preoperative and postoperative segmentation data are presented by using the boxplot function in Figure 7.  
The narrower range of interquartile is found in postoperative cases. Two DSC values are out of the DSC range in postoperative cases and are marked as outliers. \begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline  & \begin{tabular}{c} **Itraclass** \\ **Correlation** \\ \end{tabular} & \begin{tabular}{c} **95\% Confidence Interval** \\ **Lower Bound** \\ \end{tabular} & \begin{tabular}{c} **F Test with** \\ **Value** \\ \end{tabular} & \begin{tabular}{c} **True Value 0** \\ **Adj1** \\ \end{tabular} \\ \hline \
\begin{tabular}{l} Single measures \\ preoperative \\ \end{tabular} & 0.958 & 0.896 & 0.983 & 49.03 & 19 & 19 & 0.000 \\ \hline
\begin{tabular}{l} Single measures \\ postoperative \\ \end{tabular} & 0.931 & 0.836 & 0.972 & 27.43 & 19 & 19 & 0.000 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Results of Intraclass Correlation Coefficient (ICC) using single rater, absolute agreement and 2-way random effects model. Figure 6: Distributions of RMS values of preoperative and postoperative segmentation data. (3) The ADE values were calculated and divided into three groups: general average, positive average and negative average. The whole results are presented in Table 2.  
The mean value of computational time to perform an automatic segmentation by using all CBCT data sets was 46 s. Compared with other studies, this computation time is very fast. The achieved results are compared with the results of other similar studies. The comparison is presented in Table 2.  
DSC is the most popular metric in order to prove the accuracy of segmentation. Achieved values of DSC were similar in comparison with other studies (values were near 0.9). ADE also is a frequent metric in order to evaluate the segmentation. In our study, ADE was calculated and divided into three groups. The results between ADE values in different groups (preoperative and postoperative) were compared. It was found that differences were similar (Table 2). In comparison with the other studies, in which the proposed method was used, ADE values were found lower. The proposed method showed a short computation time to an automatic segmentation performance. The comparison of segmentation results by using automatic and surgeon methods are shown in Figure 8.  
The results of segmentation by using the proposed method showed that bones with low density were not fully segmented. However, areas of condibles and sinuses were segmented with fewer holes by using the proposed method, compared to the surgeon segmentation results (Figure 8).