Duy Nguyen The, Lamecker Hans, Kainmueller Dagmar, Zachow Stefan
Zuse-Institute Berlin, Germany.
Med Image Comput Comput Assist Interv. 2012;15(Pt 1):609-16. doi: 10.1007/978-3-642-33415-3_75.
We propose a fully automatic method for tooth detection and classification in CT or cone-beam CT image data. First we compute an accurate segmentation of the maxilla bone. Based on this segmentation, our method computes a complete and optimal separation of the row of teeth into 16 subregions and classifies the resulting regions as existing or missing teeth. This serves as a prerequisite for further individual tooth segmentation. We show the robustness of our approach by providing extensive validation on 43 clinical head CT scans.
我们提出了一种用于在CT或锥形束CT图像数据中进行牙齿检测和分类的全自动方法。首先，我们计算上颌骨的精确分割。基于此分割，我们的方法将牙齿行完整且最优地分离为16个子区域，并将所得区域分类为存在或缺失的牙齿。这是进一步进行单颗牙齿分割的前提条件。我们通过对43例临床头部CT扫描进行广泛验证，展示了我们方法的稳健性。
