Journal article
Comparison and evaluation of methods for liver segmentation from CT datasets
IEEE transactions on medical imaging, Vol.28(8), pp.1251-1265
08/2009
DOI: 10.1109/TMI.2009.2013851
PMID: 19211338
Abstract
This paper presents a comparison study between 10 automatic and six interactive methods for liver segmentation from contrast-enhanced CT images. It is based on results from the "MICCAI 2007 Grand Challenge" workshop, where 16 teams evaluated their algorithms on a common database. A collection of 20 clinical images with reference segmentations was provided to train and tune algorithms in advance. Participants were also allowed to use additional proprietary training data for that purpose. All teams then had to apply their methods to 10 test datasets and submit the obtained results. Employed algorithms include statistical shape models, atlas registration, level-sets, graph-cuts and rule-based systems. All results were compared to reference segmentations five error measures that highlight different aspects of segmentation accuracy. All measures were combined according to a specific scoring system relating the obtained values to human expert variability. In general, interactive methods reached higher average scores than automatic approaches and featured a better consistency of segmentation quality. However, the best automatic methods (mainly based on statistical shape models with some additional free deformation) could compete well on the majority of test images. The study provides an insight in performance of different segmentation approaches under real-world conditions and highlights achievements and limitations of current image analysis techniques.
Details
- Title: Subtitle
- Comparison and evaluation of methods for liver segmentation from CT datasets
- Creators
- Tobias Heimann - Division of Medical and Biological Informatics, German Cancer Research Center, 69121 Heidelberg, Germany. t.heimann@dkfz.deChristian BauerBram van GinnekenReinhard BeichelMartin A StynerYulia ArzhaevaVolker AurichAndreas BeckChristoph BeckerGyörgy BekesFernando BelloGerd BinnigHorst BischofAlexander BornikPeter M M CashmanYing ChiAndrés CordovaBenoit M DawantMárta FidrichJacob D FurstDaisuke FurukawaLars GrenacherJoachim HorneggerDagmar KainmüllerRichard I KitneyHidefumi KobatakeHans LameckerThomas LangeJeongjin LeeBrian LennonRui LiSenhu LiHans-Peter MeinzerGábor NemethDaniela S RaicuAnne-Mareike RauEva M van RikxoortMikaël RoussonLászló RuskoKinda A SaddiGünter SchmidtDieter SeghersAkinobu ShimizuPieter SlagmolenErich SorantinGrzegorz SozaRuchaneewan SusomboonJonathan M WaiteAndreas WimmerIvo Wolf
- Resource Type
- Journal article
- Publication Details
- IEEE transactions on medical imaging, Vol.28(8), pp.1251-1265
- DOI
- 10.1109/TMI.2009.2013851
- PMID
- 19211338
- NLM abbreviation
- IEEE Trans Med Imaging
- ISSN
- 0278-0062
- eISSN
- 1558-254X
- Publisher
- Institute of Electrical and Electronics Engineers
- Language
- English
- Date published
- 08/2009
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984083229402771
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