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Med Image Anal. 2010 Dec;14(6):707-22. doi: 10.1016/j.media.2010.05.005. Epub 2010 Jun 4.

Comparing and combining algorithms for computer-aided detection of pulmonary nodules in computed tomography scans: The ANODE09 study.

Author information

1
Image Sciences Institute, University Medical Center Utrecht, The Netherlands. bram@isi.uu.nl

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.

PMID:
20573538
DOI:
10.1016/j.media.2010.05.005
[Indexed for MEDLINE]

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