Tooth segmentation plays an important role in computer-aided orthodontics. However, many published approaches directly separate teeth from dental mesh without dealing with the region fusion, which leads to inaccurate results and incomplete segmented teeth with side shape lacked. Meanwhile, existing tooth shape modeling schemes are interaction-intensive and inefficient. To resolve this problem, a new tooth segmentation approach based on segmentation of feature line was proposed. Feature region was selected according to mean curvature, and morphologic algorithm was used to extract dentition line. The fusion region was automatically recognized by the feature line segmenting and branch points matching algorithm as well as morphologic dilation. The restoration result was automatically obtained by repairing holes with matched branch points. After the gingival margin lines between adjacent teeth were extracted, the teeth were segmented by all the gingival margin lines. Experimental results demonstrate that the poposed approach is accurate, the segmented teeth have complete side feature. In addition, the approach avoids user interactions in the stage of tooth shape modeling, thus improving the whole efficience by 60%-90% compared with the method which manually identifies and removes the interdental adhesion area and reconstructs the missing tooth surface by surface energy constraint.