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Conference Paper: Automatic boundary extraction and rectification of bony tissue in CT images using artificial intelligence techniques

TitleAutomatic boundary extraction and rectification of bony tissue in CT images using artificial intelligence techniques
Authors
KeywordsBoundary extraction
Boundary rectification
CT
Artificial intelligence
Thresholding
Reconstruction
Issue Date2000
PublisherSPIE - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/app/Publications/index.cfm?fuseaction=proceedings
Citation
SPIE Conference on Medical Imaging 2000: Image Processing, San Diego, CA., 14 February 2000. In SPIE - International Society for Optical Engineering Proceedings, 2000, v. 3979, p. 896-905 How to Cite?
AbstractA novel approach is presented for fully automated boundary extraction and rectification of bony tissue from planar CT data. The approach extracts and rectifies feature boundary in a hierarchical fashion. It consists of a fuzzy multilevel thresholding operation, followed by a small void cleanup procedure. Then a binary morphological boundary detector is applied to extract the boundary. However, defective boundaries and undesirable artifacts may still be present. Thus two innovative anatomical knowledge based algorithms are used to remove the undesired structures and refine the erroneous boundary. Results of applying the approach on lumbar CT images are presented, with a discussion of the potential for clinical application of the approach.
Persistent Identifierhttp://hdl.handle.net/10722/54094
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorKwan, FYen_HK
dc.contributor.authorCheung, KCen_HK
dc.contributor.authorGibson, Ien_HK
dc.date.accessioned2009-04-03T07:36:37Z-
dc.date.available2009-04-03T07:36:37Z-
dc.date.issued2000en_HK
dc.identifier.citationSPIE Conference on Medical Imaging 2000: Image Processing, San Diego, CA., 14 February 2000. In SPIE - International Society for Optical Engineering Proceedings, 2000, v. 3979, p. 896-905en_HK
dc.identifier.issn0277-786Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/54094-
dc.description.abstractA novel approach is presented for fully automated boundary extraction and rectification of bony tissue from planar CT data. The approach extracts and rectifies feature boundary in a hierarchical fashion. It consists of a fuzzy multilevel thresholding operation, followed by a small void cleanup procedure. Then a binary morphological boundary detector is applied to extract the boundary. However, defective boundaries and undesirable artifacts may still be present. Thus two innovative anatomical knowledge based algorithms are used to remove the undesired structures and refine the erroneous boundary. Results of applying the approach on lumbar CT images are presented, with a discussion of the potential for clinical application of the approach.-
dc.languageengen_HK
dc.publisherSPIE - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/app/Publications/index.cfm?fuseaction=proceedingsen_HK
dc.relation.ispartofSPIE - International Society for Optical Engineering Proceedings-
dc.rightsCopyright 2000 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited. This article is available online at https://doi.org/10.1117/12.387755-
dc.subjectBoundary extraction-
dc.subjectBoundary rectification-
dc.subjectCT-
dc.subjectArtificial intelligence-
dc.subjectThresholding-
dc.subjectReconstruction-
dc.titleAutomatic boundary extraction and rectification of bony tissue in CT images using artificial intelligence techniquesen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0277-786X&volume=3979&spage=896&epage=905&date=2000&atitle=Automatic+boundary+extraction+and+rectification+of+bony+tissue+in+CT+images+using+artificial+intelligence+techniquesen_HK
dc.identifier.emailCheung, KC: kccheung@hkucc.hku.hken_HK
dc.identifier.emailGibson, I: igibson@hkucc.hku.hken_HK
dc.identifier.authorityCheung, KC=rp01322-
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1117/12.387755-
dc.identifier.scopuseid_2-s2.0-0033699736-
dc.identifier.hkuros49313-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0033699736&selection=ref&src=s&origin=recordpage-
dc.identifier.volume3979-
dc.identifier.spage896-
dc.identifier.epage905-
dc.publisher.placeUnited States-
dc.identifier.scopusauthoridKwan, Matthew FY=7005364457-
dc.identifier.scopusauthoridCheung, KC=7402406698-
dc.identifier.scopusauthoridGibson, Ian=15831816500-
dc.customcontrol.immutablesml 151026 - merged-

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