DEVELOPMENT OF COMPUTER-AIDED DIAGNOSTIC SYSTEM USING X-RAY IMAGE FEACHER ANALYSIS

本文从医学X射线成像的各个物理机制出发，提出了一些抑制光学模糊和量子斑点的方法。首先利用激光扫描仪的传输特性、胶片的特性曲线、光密度的对数变换和基于点扩散函数的伪逆滤波器确定性地去除光学模糊。其次，从Bayrs定理出发，推导出了两种剩余量子斑驳的恢复方法。一个是利用量子斑点的统计特性的随机型宽灵敏数字滤波器。另一个是一个新的扩展回归模型，可能有一点信息缺乏和一个简单的实验回归模型。因此，量子斑点在统计学上被去除。一个计算机辅助诊断（CAD）系统，使用这些过滤器的开发和应用于口腔放射学。登蒂 ...更多信息 口腔颌面部老年性囊肿、牙源性角化囊肿和成釉细胞瘤是常见病，但其治疗方法各不相同。然后，有必要作出准确的鉴别诊断，虽然他们的症状彼此相似。作为一项试点研究，我们调查了使用逻辑回归和神经网络的统计方法。根据这些研究，我们在1995年7月日本医学物理学会第12届年会上发表了“口腔放射学中的神经网络鉴别诊断和统计分析”。并在1995年9月第36届日本口腔颌面放射学会年会上发表了“用统计学方法和神经网络对含牙囊肿、牙源性角化囊肿和成釉细胞瘤进行放射学鉴别诊断”的论文。在此基础上，我们于1996年建立了系统并积累了数据。1996年9月在第37届日本口腔颌面放射学会年会上发表了“使用专家系统进行牙区放射学鉴别诊断”的论文。最后，我们在广岛大学对所开发的系统进行了临床评价，即牙科医生对这些方法的有效性进行了评价和确认。本研究提出的方法也应用于牙齿图像的其他区域。少

In this study, some restration methods for the x -ray images with optical blurs and quantum mottles were developed by considering each physical mechanism of the medical x-ray image formation. More specifically, the optical blurs were first deterministically cleared away by using the transfer characteristic of the laser scanner, the characteristic curve of the film, the logarithmic transformation of the optical density and a pseud-invers filter based on the point spread function. Next, two restoration methods for remaining quantum mottles were derived from the basis of a Bayrs' theorem. One was a wide sensive digital filter of a stochastic type using the statistical properties of quantum mottles. Another was a new extended regression model that might have a little information lack and a simple experimental regression model. Thus, the quantum mottles were statistically removed. A computer-aided diagnostic (CAD) system using these filters is developed and applied for oral radiology. Denti … More gerous cyst, odontogenic keratocyst and ameloblastoma in maxillofacial region occur frequently, but their recuperations are diffrent. Then it is necessary to make an exact differential diagnosis, although their symptoms are similar to one another. As a pilot study, we investigated statistical methods using a logistic regression and neural network. Under these studies, we presented as "Differential diagnosis by neural network and statistical analysis in oral radiology" in the 12th Annual eeting Japanese Association of Medical Physics in July 1995. And, we also presented as "Radiographic differential diagnosis among dentigerous cyst, odontogenic keratocyst and ameloblastma using statistical methods and neural networrk" in the 36th Japanese Society for Oral and Maxillofacial Radiology Annual meeting in September 1995. Based on these results, in 1996, we constructed the system and accumulated data. Kodera presented as "Radiographic differentiial diagnosis in dental region using expert system" in teh 37th Japanese Society for Oral and Maxillofacial Radiology Annual meeting in September 1996. Finally, we evaluated clinically the developed system in HIroshima University, namely dentists evaluated and confirmed the deffectiveness of these methods. The method proposed in this study was applied to the other area in dental images. Less