Evaluation of a neural network classifier for pancreatic masses based on CT findings
- 作者：Ikeda ; Mitsuru ; Ito ; Shigeki ; Ishigaki ; Takeo ; Yamauchi ; Kazunobu
- 关键词：Computer aided diagnosis ; Neural network ; Receiver operating characteristic curve (ROC) ; Radiology and radiologists ; Pancreas
- 刊名：Computerized Medical Imaging and Graphics
- 出版年：1997
- 期刊代码：69_08956111
- 类别：med
- 出版时间：May 6, 1997
- 卷：21
- 期：3
- 页码：175-183
- 文件大小：898 K
摘要
We have investigated a neural network classifier based on CT findings extracted by a radiologist for the differential diagnosis between the pancreatic ductal adenocarcinoma and mass-forming pancreatitis, and compared its classification performance with that of Bayesian analysis, Hayashi's quantification method II, and radiologists. The three computerized classification methods were designed to classify categorized CT findings extracted by a radiologist, and were trained and tested on 71 cases. There was comparable performance between the neural the network, the Bayesian analysis, Hayashi's quantification method II, and the radiologists, in classifying pancreatic carcinoma and inflammatory mass.