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dc.contributor.author
Valenzuela, Waldo
dc.contributor.author
Ferguson, Stephen J.
dc.contributor.author
Ignasiak, Dominika
dc.contributor.author
Diserens, Gaëlle
dc.contributor.author
Häni, Levin
dc.contributor.author
Wiest, Roland
dc.contributor.author
Vermathen, Peter
dc.contributor.author
Boesch, Chris
dc.contributor.author
Reyes, Mauricio
dc.date.accessioned
2018-11-01T13:27:27Z
dc.date.available
2017-06-12T07:30:36Z
dc.date.available
2018-11-01T13:27:27Z
dc.date.issued
2016-05-25
dc.identifier.issn
1932-6203
dc.identifier.other
10.1371/journal.pone.0156035
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/117382
dc.identifier.doi
10.3929/ethz-b-000117382
dc.description.abstract
Background and Purpose In clinical diagnosis, medical image segmentation plays a key role in the analysis of pathological regions. Despite advances in automatic and semi-automatic segmentation techniques, time-effective correction tools are commonly needed to improve segmentation results. Therefore, these tools must provide faster corrections with a lower number of interactions, and a user-independent solution to reduce the time frame between image acquisition and diagnosis. Methods We present a new interactive method for correcting image segmentations. Our method provides 3D shape corrections through 2D interactions. This approach enables an intuitive and natural corrections of 3D segmentation results. The developed method has been implemented into a software tool and has been evaluated for the task of lumbar muscle and knee joint segmentations from MR images. Results Experimental results show that full segmentation corrections could be performed within an average correction time of 5.5±3.3 minutes and an average of 56.5±33.1 user interactions, while maintaining the quality of the final segmentation result within an average Dice coefficient of 0.92±0.02 for both anatomies. In addition, for users with different levels of expertise, our method yields a correction time and number of interaction decrease from 38±19.2 minutes to 6.4±4.3 minutes, and 339±157.1 to 67.7±39.6 interactions, respectively.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Public Library of Science
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.title
FISICO: Fast Image SegmentatIon COrrection
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
ethz.journal.title
PLoS ONE
ethz.journal.volume
11
en_US
ethz.journal.issue
5
en_US
ethz.journal.abbreviated
PLoS ONE
ethz.pages.start
e0156035
en_US
ethz.size
17 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.identifier.nebis
006206116
ethz.publication.place
San Francisco, CA, USA
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02070 - Dep. Gesundheitswiss. und Technologie / Dep. of Health Sciences and Technology::02518 - Institut für Biomechanik / Institute for Biomechanics::03915 - Ferguson, Stephen / Ferguson, Stephen
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02070 - Dep. Gesundheitswiss. und Technologie / Dep. of Health Sciences and Technology::02518 - Institut für Biomechanik / Institute for Biomechanics::03915 - Ferguson, Stephen / Ferguson, Stephen
ethz.date.deposited
2017-06-12T07:33:20Z
ethz.source
ECIT
ethz.identifier.importid
imp593654780930e90447
ethz.ecitpid
pub:179284
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-15T08:00:20Z
ethz.rosetta.lastUpdated
2018-11-01T13:27:43Z
ethz.rosetta.versionExported
true
ethz.COinS
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