Automated detection of lung nodules in low-dose computed tomography
dc.contributor.author | Cascio, D | en |
dc.contributor.author | Cheran, SC | en |
dc.contributor.author | Chincarini, A | en |
dc.contributor.author | Nunzio, GD | en |
dc.contributor.author | Delogu, P | en |
dc.contributor.author | Fantacci, ME | en |
dc.contributor.author | Gargano, G | en |
dc.contributor.author | Gori, I | en |
dc.contributor.author | Masala, GL | en |
dc.contributor.author | Martinez, AP | en |
dc.contributor.author | Retico, A | en |
dc.contributor.author | Santoro, M | en |
dc.contributor.author | Spinelli, C | en |
dc.contributor.author | Tarantino, T | en |
dc.date.accessioned | 2016-11-11T10:25:55Z | |
dc.date.available | 2016-11-11T10:25:55Z | |
dc.date.issued | 2007-07-18 | en |
dc.identifier.uri | http://hdl.handle.net/10026.1/6722 | |
dc.description | 4 pages, 2 figures: Proceedings of the Computer Assisted Radiology and Surgery, 21th International Congress and Exhibition, Berlin, Volume 2, Supplement 1, June 2007, pp 357-359 | en |
dc.description.abstract |
A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector computed-tomography (CT) images has been 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, consisting in a 3D dot-enhancement filter for nodule detection 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 database used in this study consists of 17 low-dose CT scans reconstructed with thin slice thickness (~300 slices/scan). The preliminary results are shown in terms of the FROC analysis reporting a good sensitivity (85% range) for both internal and sub-pleural nodules at an acceptable level of false positive findings (1-9 FP/scan); the sensitivity value remains very high (75% range) even at 1-6 FP/scan | en |
dc.language.iso | en | en |
dc.subject | physics.med-ph | en |
dc.subject | physics.med-ph | en |
dc.title | Automated detection of lung nodules in low-dose computed tomography | en |
dc.type | Journal Article | |
plymouth.author-url | http://arxiv.org/abs/0707.2696v1 | en |
plymouth.journal | Proceedings of the Computer Assisted Radiology and Surgery | en |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics | |
dcterms.dateAccepted | 2007-07-01 | en |
dc.rights.embargoperiod | Not known | en |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | en |
rioxxterms.licenseref.startdate | 2007-07-18 | en |
rioxxterms.type | Journal Article/Review | en |