Journal article
Extraction of Airways From CT (EXACT'09)
IEEE transactions on medical imaging, Vol.31(11), pp.2093-2107
11/2012
DOI: 10.1109/TMI.2012.2209674
PMID: 22855226
Abstract
This paper describes a framework for establishing a reference airway tree segmentation, which was used to quantitatively evaluate 15 different airway tree extraction algorithms in a standardized manner. Because of the sheer difficulty involved in manually constructing a complete reference standard from scratch, we propose to construct the reference using results from all algorithms that are to be evaluated. We start by subdividing each segmented airway tree into its individual branch segments. Each branch segment is then visually scored by trained observers to determine whether or not it is a correctly segmented part of the airway tree. Finally, the reference airway trees are constructed by taking the union of all correctly extracted branch segments. Fifteen airway tree extraction algorithms from different research groups are evaluated on a diverse set of 20 chest computed tomography (CT) scans of subjects ranging from healthy volunteers to patients with severe pathologies, scanned at different sites, with different CT scanner brands, models, and scanning protocols. Three performance measures covering different aspects of segmentation quality were computed for all participating algorithms. Results from the evaluation showed that no single algorithm could extract more than an average of 74% of the total length of all branches in the reference standard, indicating substantial differences between the algorithms. A fusion scheme that obtained superior results is presented, demonstrating that there is complementary information provided by the different algorithms and there is still room for further improvements in airway segmentation algorithms.
Details
- Title: Subtitle
- Extraction of Airways From CT (EXACT'09)
- Creators
- Pechin Lo - University of CopenhagenJoseph M Reinhardt - University of IowaBram van Ginneken - Radboud University Medical CenterChristian Bauer - Graz University of TechnologyReinhard Beichel - University of IowaTarunashree Yavarna - University of IowaEric A Hoffman - University of IowaPim A de Jong - Utrecht UniversityBenjamin Irving - University College LondonCatalin Fetita - Evry (Norway)Margarete Ortner - Evry (Norway)Rômulo Pinho - Léon Bérard Cancer Centre, Univeristy of Lyon, Lyon, FranceJan Sijbers - University of AntwerpMarco Feuerstein - Technische Universität MünchenAnna Fabijanska - University of ŁódźCarlos S Mendoza - Universidad de SevillaRafael Wiemker - PhilipsJaesung Lee - Cornell UniversityAnthony P Reeves - Cornell UniversityOliver Weinheimer - Johannes Gutenberg University MainzSilvia Born - Leipzig UniversityEva M van Rikxoort - Radboud University Medical CenterJuerg Tschirren - Vida Diagnostics (United States)Ken Mori - Nagoya UniversityBenjamin Odry - SiemensDavid P Naidich - New York UniversityIeneke Hartmann - Erasmus MCMathias Prokop - Radboud University Medical CenterJesper H Pedersen - Copenhagen University HospitalMarleen de Bruijne - University of Copenhagen
- Resource Type
- Journal article
- Publication Details
- IEEE transactions on medical imaging, Vol.31(11), pp.2093-2107
- DOI
- 10.1109/TMI.2012.2209674
- PMID
- 22855226
- NLM abbreviation
- IEEE Trans Med Imaging
- ISSN
- 0278-0062
- eISSN
- 1558-254X
- Publisher
- Institute of Electrical and Electronics Engineers
- Language
- English
- Date published
- 11/2012
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Internal Medicine
- Record Identifier
- 9984196995102771
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