Tooth Recognition in X-Ray Dental Panoramic Images with Prosthetic Detection

Kazunori Oka, Anas M. Ali, Daisuke Fujita, Syoji Kobashi
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引用次数: 1

Abstract

In the current dental practice, many panoramic dental images of the oral cavity are taken by x-ray radiograph. Using the dental panoramic images, a physician or dental assistant records dental chart. These burdens can deteriorate the quality of medical care, such as erroneous entries. Therefore, automatic analysis of panoramic dental images is desired. We have previously proposed a teeth recognition method based on Faster R-CNN and an optimization approach that performed a 94.2% accuracy. However, it shows a relatively low accuracy in panoramic images with prostheses. This paper proposed a new method to improve the accuracy by detecting prostheses separately. It first detects four types of prosthetic teeth using YOLOv5. Then, it recognizes the teeth and the prosthetic teeth simultaneously based on the proposed optimization approach using a prior knowledge model. The proposed method achieved a maximum recognition accuracy of 97.17%. It shows the usefulness of optimization using prior knowledge models in combination with prosthetic tooth detection.
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基于假体检测的x射线牙齿全景图像中的牙齿识别
在目前的牙科实践中,许多口腔全景图像都是通过x光片拍摄的。利用牙科全景图像,医生或牙科助理记录牙科图表。这些负担会降低医疗服务的质量,例如错误的记录。因此,需要对牙科全景图像进行自动分析。我们之前提出了一种基于Faster R-CNN和优化方法的牙齿识别方法,其准确率为94.2%。然而,它在带有假体的全景图像中显示出相对较低的精度。本文提出了一种通过对假体进行单独检测来提高检测精度的新方法。它首先使用YOLOv5检测四种类型的假牙。在此基础上,利用先验知识模型实现了假牙和真牙的同时识别。该方法的最高识别准确率为97.17%。结果表明,将先验知识模型与义齿检测相结合进行优化是有效的。
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