论文标题
使用U-NET和形态加工对全景牙齿X射线照片进行牙齿实例分割
Tooth Instance Segmentation on Panoramic Dental Radiographs Using U-Nets and Morphological Processing
论文作者
论文摘要
全景X射线图像中的自动牙齿分割是牙科图像分析的重要研究主题。在这项研究中，我们提出了一个后处理阶段，以获取一个分割图，其中图像中的对象分开，并将此技术应用于U-NET网络中的牙齿实例分割。后处理由灰度形态和过滤操作组成，这些操作应用于在二进制之前应用于网络的Sigmoid输出。在整体牙齿分割中，获得了95.4-0.3％的骰子重叠分数。提出的后处理阶段将牙齿计数的平均误差降低到6.15％，而没有后处理的误差为26.81％。据我们所知，分割和牙齿计数的性能在文献中都是最高的。此外，这是通过使用相对较小的培训数据集来实现的，该数据集由105张图像组成。尽管这项研究的目的是分割牙齿实例，但提出的方法适用于其他领域的类似问题，例如分开细胞实例
Automatic teeth segmentation in panoramic x-ray images is an important research subject of the image analysis in dentistry. In this study, we propose a post-processing stage to obtain a segmentation map in which the objects in the image are separated, and apply this technique to tooth instance segmentation with U-Net network. The post-processing consists of grayscale morphological and filtering operations, which are applied to the sigmoid output of the network before binarization. A dice overlap score of 95.4 - 0.3% is obtained in overall teeth segmentation. The proposed post-processing stages reduce the mean error of tooth count to 6.15%, whereas the error without post-processing is 26.81%. The performances of both segmentation and tooth counting are the highest in the literature, to our knowledge. Moreover, this is achieved by using a relatively small training dataset, which consists of 105 images. Although the aim in this study is to segment tooth instances, the presented method is applicable to similar problems in other domains, such as separating the cell instances
