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

利用 X 射线图像 FEAHER 分析的计算机辅助诊断系统的开发

基本信息

批准号：
04454503
负责人：
WADA Takuro
金额：
$ 0.77万
依托单位：
HIROSHIMAUNIVERSITY
依托单位国家：
日本
项目类别：
Grant-in-Aid for General Scientific Research (B)
财政年份：
1992
资助国家：
日本
起止时间：
1992 至 1993
项目状态：
已结题

项目摘要

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

在这项研究中，通过考虑医学X射线图像形成的每种物理机制，开发了一些具有光学模糊和量子斑驳的X射线图像的恢复方法。更具体地说，首先通过使用转移确定性地清除光学模糊。接下来，基于激光扫描仪的特性、薄膜的特性曲线、光密度的对数变换和基于点扩散函数的伪逆滤波器，推导了两种剩余量子斑驳的恢复方法。拜尔斯定理。一个是使用量子斑驳的统计特性的宽灵敏数字滤波器，另一个是可能缺少少量信息的新的扩展回归模型，并且是一个简单的实验回归模型。最近开发了使用这些过滤器的计算机辅助诊断 (CAD) 系统，并将其应用于牙周囊肿、牙源性角化囊肿和成釉细胞瘤。颌面部经常发生，但它们的恢复情况不同，因此，尽管它们的症状相似，但有必要做出准确的鉴别诊断。作为一项试点研究，我们使用逻辑回归和神经网络研究了统计方法。 1995年7月，在日本医学物理学会第12届年会上，我们提出了“口腔放射学中的神经网络鉴别诊断和统计分析”。 1995年9月，在第36届日本口腔颌面放射学会年会上，我们提出了“使用统计方法和神经网络对囊肿、牙源性角化囊肿和成釉细胞瘤进行诊断”的研究。基于这些结果，我们于1996年构建了该系统并积累了数据。小寺提出了“放射线摄影”第37届日本口腔颌面放射线学会9月年会上的“使用专家系统的牙科区域鉴别诊断” 1996年。最后，我们对广岛大学开发的系统进行了临床评估，即牙科医生评估并证实了这些方法的有效性，并将本研究提出的方法应用于牙科图像的其他领域。