A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector helical CT images with 1.25-mm slice thickness is being developed in the framework of the INFN-supported MAGIC-5 Italian project. The basic modules of our lung-CAD system, a dot-enhancement filter for nodule candidate selection and a voxel-based neural classifier for false-positive finding reduction, are described. Preliminary results obtained on the so-far collected database of lung CT scans are discussed.
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Titolo: | Computer-aided detection of pulmonary nodules in low-dose CT |
Autori: | |
Anno: | 2007 |
Citazione: | Delogu, P., Fantacci, M., Gori, I., Martinez, A.p., & Retico, A. (2007). Computer-aided detection of pulmonary nodules in low-dose CT. In COMPUTATIONAL MODELLING OF OBJECTS REPRESENTED IN IMAGES: FUMDAMENTALS, METHODS AND APPLICATIONS (pp.165-167). |
Abstract: | A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector helical CT images with 1.25-mm slice thickness is being developed in the framework of the INFN-supported MAGIC-5 Italian project. The basic modules of our lung-CAD system, a dot-enhancement filter for nodule candidate selection and a voxel-based neural classifier for false-positive finding reduction, are described. Preliminary results obtained on the so-far collected database of lung CT scans are discussed. |
Handle: | http://hdl.handle.net/11365/1006377 |
ISBN: | 978-041543349-5 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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