Lung Nodule Detection in CT Scans

In this paper we describe a computer-aided diagnosis (CAD) system for automated detection of pulmonary nodules in computed-tomography (CT) images. After extracting the pulmonary parenchyma using a combination of image processing techniques, a region growing method is applied to detect nodules based on 3D geometric features. We applied the CAD system 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 low false-positive detection rate was achieved. Keywords--computer assisted diagnosis, medical image segmentation, shape recognition.

• Type: Conference
• Year: 2004
• Where: IJIT
• Authors: Michela Antonelli, Graziano Frosini, Beatrice Lazzerini, Francesco Marcelloni
• Keywords: Artificial Intelligence, IJIT 2004, Low False-positive Detection, Lung Cancer Detection, Pulmonary Nodules