| Literature DB >> 20573538 |
Bram van Ginneken1, Samuel G Armato, Bartjan de Hoop, Saskia van Amelsvoort-van de Vorst, Thomas Duindam, Meindert Niemeijer, Keelin Murphy, Arnold Schilham, Alessandra Retico, Maria Evelina Fantacci, Niccolò Camarlinghi, Francesco Bagagli, Ilaria Gori, Takeshi Hara, Hiroshi Fujita, Gianfranco Gargano, Roberto Bellotti, Sabina Tangaro, Lourdes Bolaños, Francesco De Carlo, Piergiorgio Cerello, Sorin Cristian Cheran, Ernesto Lopez Torres, Mathias Prokop.
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), 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. Copyright 2010 Elsevier B.V. All rights reserved.Entities:
Mesh:
Year: 2010 PMID: 20573538 DOI: 10.1016/j.media.2010.05.005
Source DB: PubMed Journal: Med Image Anal ISSN: 1361-8415 Impact factor: 8.545