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Heuristically Automatic Segmentation Technology in Dental and Maxillofacial CT Images |
College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing 210016, China
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Abstract Segmenting CT slices featured contour accurately and rapidly is an important part in the medical image 3D reconstruction. The existing contour extracting technologies have to manually extract outlines interactively layer by layer, not only timeconsuming but also low accuracy. For this limitation, this paper proposed a automatic contour extracting method for tooth segmentation based on heuristic in dental and maxillofacial CT images. First, we enhanced all the image edges with Laplace operator. Second, the contour registration mapping technology passes the outline down heuristically. Ultimately, the shrinkwrapping algorithm is used to segment the teeth outlines automatically. With 14 cases (28~32 teeth samples) of a maxillary tooth cone beam CT tomography image sequences, at the same situation, we extract the contours of the sample with our method and the traditional method respectively. We determined the time of each tooth and the average distance between extracted contour and the real contour. From the experimental result, we concluded that the average time of our automatic extracting algorithm was about 23% of the traditional interactively algorithm time. The quality with our method is similar to traditional extracted contour. This method can provide a feasible and efficient approach to automatically segment CT slices featured areas, and further provide a new idea to improve the contour automatic extracting and image 3D reconstruction algorithm.
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