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Conference Paper: Thyroid cancer cells boundary location by a fuzzy edge detection method

TitleThyroid cancer cells boundary location by a fuzzy edge detection method
Authors
Leung, CCChan, FHYLam, KYKwok, PCKChen, WF
KeywordsComputers
Artificial intelligence
Issue Date2000
PublisherIEEE, Computer Society.
Citation
The 15th International Conference on Pattern Recognition, Barcelona, Spain, 3-7 September 2000, v. 4, p. 360-363 How to Cite?
DOI: http://dx.doi.org/10.1109/ICPR.2000.902933
AbstractMorphometric assessment of tumor cells is important in the prediction of biological behavior of thyroid cancer. In order to automate the process, the computer-based system has to recognize the boundary of the cells. Many methods for the boundary detection have appeared in the literature and some of them applied to microscopic slice analysis. However, there is no reliable method since the gray-levels in the nuclei are uneven and are similar to the background. In the paper, a fuzzy edge detection method is used and is based on an improved generalized fuzzy operator. The method enhances the nuclei and effectively separates the cells from the background.
Persistent Identifierhttp://hdl.handle.net/10722/46262
ISSN
1051-4651
2020 SCImago Journal Rankings: 0.276

 

DC FieldValueLanguage
dc.contributor.authorLeung, CCen_HK
dc.contributor.authorChan, FHYen_HK
dc.contributor.authorLam, KYen_HK
dc.contributor.authorKwok, PCKen_HK
dc.contributor.authorChen, WFen_HK
dc.date.accessioned2007-10-30T06:46:02Z-
dc.date.available2007-10-30T06:46:02Z-
dc.date.issued2000en_HK
dc.identifier.citationThe 15th International Conference on Pattern Recognition, Barcelona, Spain, 3-7 September 2000, v. 4, p. 360-363en_HK
dc.identifier.issn1051-4651en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46262-
dc.description.abstractMorphometric assessment of tumor cells is important in the prediction of biological behavior of thyroid cancer. In order to automate the process, the computer-based system has to recognize the boundary of the cells. Many methods for the boundary detection have appeared in the literature and some of them applied to microscopic slice analysis. However, there is no reliable method since the gray-levels in the nuclei are uneven and are similar to the background. In the paper, a fuzzy edge detection method is used and is based on an improved generalized fuzzy operator. The method enhances the nuclei and effectively separates the cells from the background.en_HK
dc.format.extent552408 bytes-
dc.format.extent2599 bytes-
dc.format.extent13817 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE, Computer Society.en_HK
dc.rights©2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.subjectComputersen_HK
dc.subjectArtificial intelligenceen_HK
dc.titleThyroid cancer cells boundary location by a fuzzy edge detection methoden_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1051-4651&volume=4&spage=360&epage=363&date=2000&atitle=Thyroid+cancer+cells+boundary+location+by+a+fuzzy+edge+detection+methoden_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/ICPR.2000.902933en_HK
dc.identifier.hkuros60699-
dc.identifier.issnl1051-4651-

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