Automatic segmentation of teeth from dentomaxillofacial 3D-CT images

CT is an effective tool for image diagnosis because it enables noninvasive observation of internal organs. In the course of CT, 3D-CT, such as a helical scanning CT and a multi-detector row CT, has been developed. With the use of 3D-CT, organs can be observed from several viewing directions. Even now, however, 3D-CT images are generated by manual procedures to extract objective organs using the threshold method. These procedures waste time and effort. Therefore, development of highly automated and effective extracting techniques has been desired. The region growing (RG) method is one of the effective techniques of extracting internal organs. The conventional RG method, however, has some defects. Extracted regions are strongly affected by the threshold value for segmentation. A break point on a region contour yields a leakage of region. To overcome these defects, we formulated a modified region growing method with edge detection (MRGWED) which combines a three-dimensional region growing technique and an edge detection technique. Using the MRGWED, we tried to extract teeth from dentomaxillofacial 3D-CT image data.