Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/11826
Full metadata record
DC FieldValueLanguage
dc.contributor.authorAlharbi, Hajar Mohammedsaleh Hen
dc.contributor.authorKwan, Paul Hen
dc.contributor.authorSajeev, Abudulkadiren
local.source.editorEditor(s): Brendan McCane, Steven Mills, Jeremiah D Dengen
dc.date.accessioned2013-01-04T16:08:00Z-
dc.date.issued2012-
dc.identifier.citationIVCNZ '12: Proceedings of the 27th International Conference on Image and Vision Computing New Zealand, p. 330-334en
dc.identifier.isbn9781450314732en
dc.identifier.urihttps://hdl.handle.net/1959.11/11826-
dc.description.abstractSegmenting suspicious regions in mammographic images that may contain tumours from the background parenchyma of the breast is a highly challenging task. This is made difficult by factors including the complicated structure of breast tissues, unclear boundaries between normal tissues and tumours, and the low contrast between masses and surrounding regions in the images. In recent years, many researchers have discovered that fuzzy-logic based techniques have a number of advantages over conventional crisp approaches in segmenting masses in mammographic images. To this end, we compare five representative fuzzy thresholding techniques for this task in this paper using the recall and precision metrics. Experimental results revealed that fuzzy similarity thresholding achieves higher segmentation accuracy over a test set of 54 mammographic images selected from the mini-MIAS database.en
dc.languageenen
dc.publisherAssociation for Computing Machinery (ACM)en
dc.relation.ispartofIVCNZ '12: Proceedings of the 27th International Conference on Image and Vision Computing New Zealanden
dc.relation.ispartofseriesInternational Conference Proceedings Series (ICPS)en
dc.titleA Comparative Study of Fuzzy Thresholding Techniques for Mass Detection in Digital Mammographyen
dc.typeConference Publicationen
dc.relation.conferenceIVCNZ 2012: 27th International Conference on Image and Vision Computing New Zealanden
dc.subject.keywordsNeural, Evolutionary and Fuzzy Computationen
dc.subject.keywordsCancer Diagnosisen
dc.subject.keywordsImage Processingen
local.contributor.firstnameHajar Mohammedsaleh Hen
local.contributor.firstnamePaul Hen
local.contributor.firstnameAbudulkadiren
local.subject.for2008080108 Neural, Evolutionary and Fuzzy Computationen
local.subject.for2008111202 Cancer Diagnosisen
local.subject.for2008080106 Image Processingen
local.subject.seo2008890201 Application Software Packages (excl. Computer Games)en
local.subject.seo2008920102 Cancer and Related Disordersen
local.subject.seo2008970108 Expanding Knowledge in the Information and Computing Sciencesen
local.profile.schoolIT Voice Systemsen
local.profile.schoolSchool of Science and Technologyen
local.profile.schoolSchool of Science and Technologyen
local.profile.emailhalharbi@une.edu.auen
local.profile.emailwkwan2@une.edu.auen
local.profile.emailasajeev@une.edu.auen
local.output.categoryE1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordune-20121130-161929en
local.date.conference26th - 28th November, 2012en
local.conference.placeDunedin, New Zealanden
local.publisher.placeNew York, United States of Americaen
local.format.startpage330en
local.format.endpage334en
local.peerreviewedYesen
local.contributor.lastnameAlharbien
local.contributor.lastnameKwanen
local.contributor.lastnameSajeeven
dc.identifier.staffune-id:halharbien
dc.identifier.staffune-id:wkwan2en
dc.identifier.staffune-id:asajeeven
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:12027en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleA Comparative Study of Fuzzy Thresholding Techniques for Mass Detection in Digital Mammographyen
local.output.categorydescriptionE1 Refereed Scholarly Conference Publicationen
local.relation.urlhttp://www.cs.otago.ac.nz/ivcnz2012/en
local.conference.detailsIVCNZ 2012: 27th International Conference on Image and Vision Computing New Zealand, Dunedin, New Zealand, 26th - 28th November, 2012en
local.search.authorAlharbi, Hajar Mohammedsaleh Hen
local.search.authorKwan, Paul Hen
local.search.authorSajeev, Abudulkadiren
local.uneassociationUnknownen
local.year.published2012en
local.subject.for2020460203 Evolutionary computationen
local.subject.for2020321102 Cancer diagnosisen
local.subject.for2020460306 Image processingen
local.subject.seo2020220401 Application software packagesen
local.subject.seo2020280115 Expanding knowledge in the information and computing sciencesen
local.date.start2012-11-26-
local.date.end2012-11-28-
Appears in Collections:Conference Publication
School of Science and Technology
Files in This Item:
3 files
File Description SizeFormat 
Show simple item record

Page view(s)

1,316
checked on May 19, 2024
Google Media

Google ScholarTM

Check


Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.