Identification of lung nodules based on combining multi-slice CT images and clinical information

Although chest CT scans are an effective means of diagnosing lung cancer, there are still problems such as the heavy burden on physicians.To solve this problem, computer-aided diagnosis (CAD) systems are being introduced.Conventional CAD systems are based on a method that uses only image information.In this study, we propose a method for identifying nodular shadows that integrates a composite image created from multi-slice CT images and clinical information such as the patient's age, sex, and medical history in the medical record.The proposed method extracts features from the multi-section CT and clinical information, respectively, integrates the features, and then performs binary classification of nodules and vessels using a classifier.The proposed method achieved a very high accuracy of Accuracy=0.983,TPR=0.987, and FPR=0.018.