Abstract
To diagnose the diffuse lung diseases, the computed tomography (CT) images are considered as effective. In general, however, the attenuation patterns of diffuse lung diseases in the CT image are complex and various. Hence an accuracy of the diagnosis depends on doctor's experience and skill. To improve the quality of the diagnosis, another doctors' opinions should be taken into consideration in general, that is, called the "second opinion". However, it increases a burden on the doctors. In this study, we propose the method that uses the result of the image classification by computer as a second opinion to reduce their burdens. We used a Counter Propagation Network (CPN) which is a kind of artificial neural network for classification method. In the CPN, the SOM part plays a role of a feature extractor and the perceptron plays a classifier role. First, CPN handles clustering by the self-organizing map, and the similar input data are assigned to the near nodes. The label is put up by using perceptronfor this expression.
