30 March 2007 An automated system for lung nodule detection in low-dose computed tomography
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Abstract
A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 Italian project. One of the main goals of this project is to build a distributed database of lung CT scans in order to enable automated image analysis through a data and cpu GRID infrastructure. The basic modules of our lung-CAD system, a dot-enhancement filter for nodule candidate selection and a neural classifier for false-positive finding reduction, are described. The system was designed and tested for both internal and sub-pleural nodules. The results obtained on the collected database of low-dose thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.
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I. Gori, I. Gori, M. E. Fantacci, M. E. Fantacci, A. Preite Martinez, A. Preite Martinez, A. Retico, A. Retico, "An automated system for lung nodule detection in low-dose computed tomography", Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 65143R (30 March 2007); doi: 10.1117/12.709642; https://doi.org/10.1117/12.709642
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