Information de reference pour ce titreAccession Number: | 00125487-201012000-00001.
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Author: | van Ginneken, Bram a,b,*; Armato, Samuel G. III c; de Hoop, Bartjan d; van Amelsvoort-van de Vorst, Saskia d; Duindam, Thomas a; Niemeijer, Meindert a; Murphy, Keelin a; Schilham, Arnold a; Retico, Alessandra e; Fantacci, Maria Evelina e,f; Camarlinghi, Niccolo e,f; Bagagli, Francesco e,f; Gori, Ilaria e,g; Hara, Takeshi h; Fujita, Hiroshi h; Gargano, Gianfranco i,j; Bellotti, Roberto i,j; Tangaro, Sabina j; Bolanos, Lourdes k,l; De Carlo, Francesco j; Cerello, Piergiorgio k; Cheran, Sorin Cristian k; Torres, Ernesto Lopez l; Prokop, Mathias d,b
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Institution: | (a)Image Sciences Institute, University Medical Center Utrecht, The Netherlands (b)Department of Radiology, Radboud University Nijmegen Medical Centre, The Netherlands (c)Department of Radiology, University of Chicago, USA (d)Department of Radiology, University Medical Center Utrecht, The Netherlands (e)Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Pisa, Italy (f)Dipartimento di Fisica dell'Universita di Pisa, Pisa, Italy (g)Bracco Imaging S.p.A., Milano, Italy (h)Department of Intelligent Image Information, Gifu University Graduate School of Medicine, Gifu, Japan (i)Dipartimento Interateneo 'M. Merlin' dell'Univerisita degli Studi di Bari, Italy (j)Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Italy (k)Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Italy (l)Caeden, Cuba
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Title: | |
Source: | Medical Image Analysis. 14(6):707-722, December 2010.
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Abstract: | Numerous publications and commercial systems are available that deal with automatic detection of pulmonary nodules in thoracic computed tomography scans, but a comparative study where many systems are applied to the same data set has not yet been performed. This paper introduces ANODE09 ( http://anode09.isi.uu.nl- ouverture dans une nouvelle fenêtre), a database of 55 scans from a lung cancer screening program and a web-based framework for objective evaluation of nodule detection algorithms. Any team can upload results to facilitate benchmarking. The performance of six algorithms for which results are available are compared; five from academic groups and one commercially available system. A method to combine the output of multiple systems is proposed. Results show a substantial performance difference between algorithms, and demonstrate that combining the output of algorithms leads to marked performance improvements.
(C) 2010Elsevier, Inc.
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Author Keywords: | Computer-aided detection; Computed tomography; Lung nodules; Lung cancer.
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Language: | English.
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Document Type: | Article.
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Journal Subset: | Clinical Medicine. Health Professions.
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ISSN: | 1361-8415
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NLM Journal Code: | c8s, 9713490
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DOI Number: | https://dx.doi.org/10.1016/j.med...- ouverture dans une nouvelle fenêtre
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