Computer-aided detection of pulmonary nodules: a comparative study using the public LIDC/IDRI database

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dc.contributor.author Jacobs, Colin
dc.contributor.author van Rikxoort, Eva M.
dc.contributor.author Murphy, Keelin
dc.contributor.author Prokop, Mathias
dc.contributor.author Schaefer-Prokop, Cornelia M.
dc.contributor.author van Ginneken, Bram
dc.date.accessioned 2019-11-26T11:49:24Z
dc.date.available 2019-11-26T11:49:24Z
dc.date.issued 2015-10-06
dc.identifier.citation Jacobs, C., van Rikxoort, E. M., Murphy, K., Prokop, M., Schaefer-Prokop, C. M. and van Ginneken, B. (2016) 'Computer-aided detection of pulmonary nodules: a comparative study using the public LIDC/IDRI database', European Radiology, 26(7), pp. 2139-2147. doi: 10.1007/s00330-015-4030-7 en
dc.identifier.volume 26 en
dc.identifier.issued 7 en
dc.identifier.startpage 2139 en
dc.identifier.endpage 2147 en
dc.identifier.issn 0938-7994
dc.identifier.uri http://hdl.handle.net/10468/9248
dc.identifier.doi 10.1007/s00330-015-4030-7 en
dc.description.abstract Objectives: To benchmark the performance of state-of-the-art computer-aided detection (CAD) of pulmonary nodules using the largest publicly available annotated CT database (LIDC/IDRI), and to show that CAD finds lesions not identified by the LIDC’s four-fold double reading process. Methods: The LIDC/IDRI database contains 888 thoracic CT scans with a section thickness of 2.5 mm or lower. We report performance of two commercial and one academic CAD system. The influence of presence of contrast, section thickness, and reconstruction kernel on CAD performance was assessed. Four radiologists independently analyzed the false positive CAD marks of the best CAD system. Results: The updated commercial CAD system showed the best performance with a sensitivity of 82 % at an average of 3.1 false positive detections per scan. Forty-five false positive CAD marks were scored as nodules by all four radiologists in our study. Conclusions: On the largest publicly available reference database for lung nodule detection in chest CT, the updated commercial CAD system locates the vast majority of pulmonary nodules at a low false positive rate. Potential for CAD is substantiated by the fact that it identifies pulmonary nodules that were not marked during the extensive four-fold LIDC annotation process. en
dc.description.sponsorship Netherlands Organisation for Scientific Research (NWO) (Project number 639.023.207) en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Springer Berlin Heidelberg en
dc.rights © 2915, The Author(s). This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. en
dc.rights.uri http://creativecommons.org/licenses/by-nc/4.0/ en
dc.subject Computer-assisted diagnosis en
dc.subject Image interpretation en
dc.subject Computer-assisted en
dc.subject Lung cancer en
dc.subject Solitary pulmonary nodule en
dc.subject Lung en
dc.title Computer-aided detection of pulmonary nodules: a comparative study using the public LIDC/IDRI database en
dc.type Article (peer-reviewed) en
dc.internal.authorcontactother Keelin Murphy, Irish Centre for Fetal and Neonatal Translational Research, University College Cork, Cork, Ireland. +353-21-490-3000 en
dc.internal.availability Full text available en
dc.description.version Published Version en
dc.contributor.funder Nederlandse Organisatie voor Wetenschappelijk Onderzoek en
dc.contributor.funder Universität Bremen en
dc.contributor.funder MeVis Medical Solutions AG en
dc.description.status Peer reviewed en
dc.identifier.journaltitle European Radiology en
dc.identifier.eissn 1432-1084


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© 2915, The Author(s). This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Except where otherwise noted, this item's license is described as © 2915, The Author(s). This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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