Kakehbaraei Somayeh, Seyedarabi Hadi, Zenouz Ali Taghavi
Department of Biomedical Engineering, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran.
Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.
J Med Signals Sens. 2018 Apr-Jun;8(2):119-124.
Teeth segmentation is an important task in computer-aided procedures and clinical diagnosis. In this paper, we propose an accurate and robust algorithm based on watershed and morphology operators for teeth and pulp segmentation and a new approach for enamel segmentation in cone-beam computed tomography (CBCT) images. Proposed method consists of five steps: acquiring appropriate CBCT image, image enhancement, teeth segmentation using the marker-controlled watershed (MCW), enamel segmentation by global threshold, and finally, utilizing the MCW for pulp segmentation. Proposed algorithms evaluated on a dataset consisting 69 patient images. Experimental results show a high accuracy and specificity for teeth, enamel, and pulp segmentation. MCW algorithm and local threshold are accurate and robust approaches to segment tooth, enamel, and pulp tissues. Methods overcome the over-segmentation phenomenon and artifacts reduction.
牙齿分割是计算机辅助程序和临床诊断中的一项重要任务。在本文中，我们提出了一种基于分水岭和形态学算子的精确且稳健的算法，用于牙齿和牙髓分割，并提出了一种在锥束计算机断层扫描（CBCT）图像中进行牙釉质分割的新方法。所提方法包括五个步骤：获取合适的CBCT图像、图像增强、使用标记控制分水岭（MCW）进行牙齿分割、通过全局阈值进行牙釉质分割，最后利用MCW进行牙髓分割。在所提算法在一个由69幅患者图像组成的数据集上进行了评估。实验结果表明，在牙齿、牙釉质和牙髓分割方面具有较高的准确性和特异性。MCW算法和局部阈值是分割牙齿、牙釉质和牙髓组织的精确且稳健的方法。这些方法克服了过分割现象并减少了伪影。
