Application of artificial neural networks in the diagnosis of lung cancer by computed tomography

To develop a computer-aided diagnostic scheme of the CT in the diagnosis of lung cancer based on artificial neural networks (ANN) to assist radiologists in distinguishing malignant from benign pulmonary nodules. 117 CT images of pulmonary nodules (58 benign and 59 malignant) were analyzed. 21 CT radiological features of each case were carefully selected and quantified by three experienced radiologists. The 21 features and 5 clinical parameters were used as ANN input data. The result of ANNt was compared with those of logistic regression by ROC curve analysis. The diagnostic accuracy of ANN and logistic regression among all samples of the training group and test group were 96.6% and 84.6%. ANN has the potential to improve the diagnostic accuracy and helpful to radiologists in the distinguishing malignant from benign pulmonary nodules on CT images.