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Computer-assisted Diagnostic System for Ultrasonography Using Fuzzy Reasoning

使用模糊推理的计算机辅助超声诊断系统

基本信息

批准号：
07672050
负责人：
TANAKA Takemasa
金额：
$ 1.54万
依托单位：
Kyushu University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1995
资助国家：
日本
起止时间：
1995 至 1996
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-07672050/
关键词：
fuzzy reasoning computer-assisted diagnosis expert system ultrasonography Fuzzy reasoning Computer-assisted diagnosis Ultra sonography Fuzzy Reasoning Compnter-Aided Diagnosis Expert System Ultra Sono graphy

项目摘要

We have developed the computer-assisted diagnostic system for ultrasonography using fuzzy reasoning. The system was constructed to differentiate the metastatic lymph node from inflammatory ones and applied to the unskilled clinicians who were from one to three years after the graduation. To construct the system, we set up three fuzzy production rules according to the diagnostic criteria. We used max-min product composition method in fuzzy reasoning and centroid method for standard defuzzification. Furthermore, in order to simulate the experienced clinician's consideration, we referred the method of analytic hierarchy process (AHP). Consequently, the diagnostic accuracy, sensitivity, and specificity were improved.We applied some kinds of defuzzification method to the computer-assisted diagnostic system and compared the diagnostic accuracy in each application. Centroid, bisector and middle of maximum method were thought to be excellent defuzzification method for our computer-assisted diagnostic system. On the other hand, largest of maximum method was superior to any other defuzzification for the diagnostic accuracy, and smallest of maximum method was superior to the diagnostic specificity. Therefore, it was suggested that the defuzzification method should be considered and selected for clinical requirement.Moreover, we considered the relationship between the unaided score of the observer and the effect of diagnostic aid. It was indicated that these were in the intensive negative correlation and the relationship could be approximated to linear regression. It was suggested that our system was especially useful for the observers whose unaided scores were very low.

我们开发了一种基于模糊推理的超声计算机辅助诊断系统。该系统用于区分转移性淋巴结和炎性淋巴结，适用于毕业后1 - 3年的临床医生。为了构建该系统，我们根据诊断标准建立了三条模糊产生规则。在模糊推理中采用最大最小积组合法，在标准去模糊化中采用质心法。此外，为了模拟经验丰富的临床医生的考虑，我们引用了层次分析法（AHP）。因此，提高了诊断的准确性、敏感性和特异性。将各种去模糊化方法应用于计算机辅助诊断系统，并比较了各种方法的诊断准确率。质心法、平分法和最大值中点法是计算机辅助诊断系统中较好的去模糊化方法。另一方面，最大值法的诊断准确性优于其他任何去模糊化方法，最小值法的诊断特异性优于其他去模糊化方法。因此，建议根据临床需要考虑和选择去模糊化方法。此外，我们考虑了观察者的独立评分与诊断辅助效果之间的关系。结果表明，二者呈显著负相关，关系可近似为线性回归。有人建议，我们的系统对那些独立得分很低的观察员特别有用。