Automated CAD for Lung Nodule Detection using CT Scans

The main objective of this paper is to evaluate the performance of the Computer-Aided Detection (CAD) system for automatic pulmonary nodule detection in lungs in CT scan images. The CAD system is applied to CT scans collected in a screening program for lung cancer detection. Each scan consists of a sequence of about 300 slices stored in DICOM (Digital Imaging and Communications in Medicine) format. All malignant nodules were detected and a very low false-positive detection rate was achieved. The automated extraction of the pulmonary parenchyma in CT images is the most crucial step in a computer-aided diagnosis (CAD) system. In this paper we describe a method, consisting of appropriate techniques, for the automated identification of the pulmonary volume. The performance is evaluated as a fully automated computerized method for the detection of lung nodules in computed tomography (CT) scans in the identification of lung cancers that may be missed during visual interpretation.