An automated system for lung nodule detection in low-dose computed tomography

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 sc...

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Bibliographic Details
Published in:arXiv.org 2007-04
Main Authors: Gori, I, Fantacci, M E, A Preite Martinez, Retico, A
Format: Article
Language:English
Subjects:
Automation
Computation
Computed tomography
Image analysis
Medical imaging
Nodules
Tomography
Online Access:Get full text
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Summary: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.
ISSN:2331-8422
DOI:10.48550/arxiv.0704.2728