Automated quantitative diagnosis system for dental diseases by optimum image processing

许多研究报道，数字牙科成像系统的诊断准确性可与胶片相媲美。本研究的目的是利用数字数据的最佳图像显示，从数字牙科成像系统中获得最大的图像信息。进一步的目标是开发一个计算机辅助诊断系统，利用龋齿诊断算法和优化图像。得到的结果如下：1。收集数字图像数据。准备了27颗拔牙，包括不同等级的龋。采用数字口腔成像系统对两对牙齿进行x线摄影。曝光时间分为8个步骤，包括最佳曝光。将牙切成两半，在体视显微镜下观察近端组织病理学。最终诊断结果作为“金标准”。为了实现近端牙面轮廓的自动提取，提出了一种基于小波变换的近端牙面自动提取算法。该方法可以自动准确地提取近端牙面。自动龋病诊断算法：在近端间位置设置感兴趣区域（ROI）。提出了一种测量齿面垂直方向像素值变化的算法。通过沿着近端牙齿表面移动，像素值的轮廓会发生变化。沿近端牙面获得一定厚度的牙体。确定了像素值变化的几个代表性值。利用上述提取的代表性值对该系统进行自动龋病诊断的准确性评价。本系统的诊断准确性与观测者相当，并且优于某些观测者。我们认为该系统可作为近端龋诊断的计算机辅助诊断系统。

Many studies have reported that diagnostic accuracy of the digital dental imaging system is comparable to films. It may be due to the inadequate image display of the digital data The purpose of this study was to obtain maximum image information from digital dental imaging system by applying optimum image display of the digital data. Further aim was to develop a computer-assisted diagnosis system using caries diagnosis algorithm and optimized images. The results obtained are as follows.1.Collection of digital image dataTwenty-seven extracted teeth including caries of various grades were prepared. Pair of two teeth were radiographed with digital dental imaging system. Exposure time was varied in 8 steps including optimum exposure. Teeth were cut into halves and histopathology of proximal surfaces was assessed under the stereomicroscope. The final diagnoses were used as the "gold standards".2.Algorithm of automated outline extraction of proximal tooth surfaceTo detect proximal tooth surface automatically, an algorithm was developed using Wavelet transforms. It was possible to extract exact proximal tooth surface automatically by using this method.3.Algorithm of automated caries diagnosisA region of interest (ROI) was set at the interproximal position. An algorithm was developed to measure the pixel value changes vertical to the tooth surface. By moving along the proximal tooth surface, a profile of the pixel value changes. along the proximal tooth surface with certain thickness was obtained. Several representative values of the pixel value change have been determined.4.Evaluation of the diagnostic accuracy of this systemAutomated caries diagnosis was performed using the representative values extracted above. The diagnostic accuracy of the present system was comparable to that of the observers and better over some of the observers. We consider this system may be useful as a computer-assisted diagnosis system for proximal caries diagnosis.