Details

Autor(en) / Beteiligte

• Bellotti, R.
• De Carlo, F.
• Gargano, G.
• Tangaro, S.
• Cascio, D.
• Catanzariti, E.
• Cerello, P.
• Cheran, S. C.
• Delogu, P.
• De Mitri, I.
• Fulcheri, C.
• Grosso, D.
• Retico, A.
• Squarcia, S.
• Tommasi, E.
• Golosio, Bruno

Titel

A CAD system for nodule detection in low-dose lung CTs based on region growing and a new active contour model

Ist Teil von

• Medical physics (Lancaster), 2007-12, Vol.34 (12), p.4901-4910

Ort / Verlag

United States: American Association of Physicists in Medicine

Erscheinungsjahr

2007

Quelle

Wiley Online Library All Journals

Beschreibungen/Notizen

• 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.