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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/18745
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dc.contributor.authorShan, X-
dc.contributor.authorDu, C-
dc.contributor.authorChen, Y-
dc.contributor.authorNandi, A-
dc.contributor.authorGong, X-
dc.contributor.authorMa, C-
dc.contributor.authorYang, P-
dc.date.accessioned2019-07-16T15:45:03Z-
dc.date.available2018-06-21-
dc.date.available2019-07-16T15:45:03Z-
dc.date.issued2017-
dc.identifier.citationICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, 2018, pp. 2367 - 2371en_US
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/18745-
dc.format.extent2367 - 2371-
dc.language.isoenen_US
dc.sourceICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery-
dc.sourceICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery-
dc.subjectComponenten_US
dc.subjectPancreas segmentationen_US
dc.subjectDixon water magnetic resonance imageen_US
dc.subjectOtsu methoden_US
dc.subjectMorphological methoden_US
dc.titleThreshold algorithm for pancreas segmentation in Dixon water magnetic resonance imagesen_US
dc.typeConference Paperen_US
dc.identifier.doihttp://dx.doi.org/10.1109/FSKD.2017.8393142-
dc.relation.isPartOfICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery-
pubs.publication-statusPublished-
Appears in Collections:Dept of Electronic and Electrical Engineering Research Papers

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