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.
Delogu, P., Fantacci, M.E., 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). Londra : Taylor & Francis.
Computer-aided detection of pulmonary nodules in low-dose CT
Delogu, P.;
2007-01-01
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.
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https://hdl.handle.net/11365/1006377
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