Hildebolt C F, Vannier M W
Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63130.
J Periodontol. 1988 Feb;59(2):87-94. doi: 10.1902/jop.1988.59.2.87.
The feasibility of applying a prototype, computer-based pattern recognition system to the objective classification of periodontal disease using dental radiographs was tested. Twenty-nine observer-classified bitewing radiographs, representing seven individuals with varying grades of periodontal disease, were selected. The radiographs were digitized using a computer-controlled TV camera. Mathematical features of these radiographs were interactively extracted using a digital image processing system (International Imaging Systems Model 75 and System/575). The features extracted from these radiographs included the brightness levels of cortical and trabecular bone and ratios of bone-loss to linear-crown height. Twenty-eight mathematically defined features (variables) were determined for each radiograph. Stepwise linear discriminant analysis used these features to classify subjects based on the presence and extent of periodontal disease. This pattern recognition system was able to grade periodontal disease in our test series with percentages of correct classifications ranging from 78.8% to 91%. This technology is particularly applicable to the development of morbidity and activity indices for periodontal diseases.
对一种基于计算机的原型模式识别系统应用于利用牙科X光片对牙周疾病进行客观分类的可行性进行了测试。选取了29张经观察者分类的咬合翼片X光片，代表了7名患有不同程度牙周疾病的个体。使用计算机控制的电视摄像机将X光片数字化。利用数字图像处理系统（国际成像系统75型和575型系统）交互式提取这些X光片的数学特征。从这些X光片中提取的特征包括皮质骨和小梁骨的亮度水平以及骨丧失与牙冠线性高度的比率。为每张X光片确定了28个数学定义的特征（变量）。逐步线性判别分析利用这些特征根据牙周疾病的存在和程度对受试者进行分类。在我们的测试系列中，这种模式识别系统能够对牙周疾病进行分级，正确分类的百分比在78.8%至91%之间。这项技术特别适用于牙周疾病发病率和活动指数的开发。
