A CAD system for nodule detection in low-dose lung CTs based on Region Growing and a new Active Contour Model

A computer-aided detection CAD system for the selection of lung nodules in computer tomography CT images is presented. The system is based on region growing RG algorithms and a new active contour model ACM, implementing a local convex hull, able to draw the correct contour of the lung parenchyma and to include the pleural nodules. The CAD consists of three steps: 1) the lung parenchymal volume is segmented by means of a RG algorithm; the pleural nodules are included through the new ACM technique; 2) a RG algorithm is iteratively applied to the previously segmented volume in order to detect the candidate nodules; 3) a double-threshold cut and a neural network are applied to reduce the false positives FPs. After having set the parameters on a clinical CT, the system works on whole scans, without the need for any manual selection. The CT database was recorded at the Pisa center of the ITALUNG-CT trial, the first Italian randomized controlled trial for the screening of the lung cancer. The detection rate of the system is 88.5% with 6.6 FPs/CT on 15 CT scans about 4700 sectional images with 26 nodules: 15 internal and 11 pleural. A reduction to 2.47 FPs/CT is achieved at 80% efficiency.