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Conference Paper: Image registration in intra-oral radiography

TitleImage registration in intra-oral radiography
Authors
KeywordsDigital subtraction radiography
Euler-Lagrange equations
Image registration
Issue Date2005
PublisherIEEE.
Citation
27th Annual International Conference of the Engineering in Medicine and Biology Society (IEEE-EMBS 2005), Shanghai, China, 1-4 September 2005. In Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, 2005, p. 3206-3209 How to Cite?
AbstractImage registration is one of the image processing methods which is widely used in computer vision, pattern recognition, and medical imaging. In digital subtraction radiography, image registration is one of the important prerequisites to match the reference and subsequent images. In this paper, we propose an automatic non-rigid registration method namely curvature-based registration that relies on a curvature based penalizing term and its application on dental radiography. The regularizing term of this intensity-based registration approach provides affine linear transformation so that pre-registration step is no longer necessary. This leads to faster and more reliable solutions. The implementation of this approach is based on the numerical solution of the underlying Euler-Lagrange equations. In addition, a comparison between this algorithm and Linear Alignment Method (LAM) with 20 image pairs is presented. © 2005 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/45857
ISSN
2023 SCImago Journal Rankings: 0.340
References

 

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dc.contributor.authorLeung, CCen_HK
dc.contributor.authorYiu, KLen_HK
dc.contributor.authorZee, KYen_HK
dc.contributor.authorTsui, WKen_HK
dc.date.accessioned2007-10-30T06:37:03Z-
dc.date.available2007-10-30T06:37:03Z-
dc.date.issued2005en_HK
dc.identifier.citation27th Annual International Conference of the Engineering in Medicine and Biology Society (IEEE-EMBS 2005), Shanghai, China, 1-4 September 2005. In Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, 2005, p. 3206-3209en_HK
dc.identifier.issn0589-1019en_HK
dc.identifier.urihttp://hdl.handle.net/10722/45857-
dc.description.abstractImage registration is one of the image processing methods which is widely used in computer vision, pattern recognition, and medical imaging. In digital subtraction radiography, image registration is one of the important prerequisites to match the reference and subsequent images. In this paper, we propose an automatic non-rigid registration method namely curvature-based registration that relies on a curvature based penalizing term and its application on dental radiography. The regularizing term of this intensity-based registration approach provides affine linear transformation so that pre-registration step is no longer necessary. This leads to faster and more reliable solutions. The implementation of this approach is based on the numerical solution of the underlying Euler-Lagrange equations. In addition, a comparison between this algorithm and Linear Alignment Method (LAM) with 20 image pairs is presented. © 2005 IEEE.en_HK
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dc.format.mimetypeapplication/pdf-
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dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofProceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conferenceen_HK
dc.rights©2005 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.subjectDigital subtraction radiographyen_HK
dc.subjectEuler-Lagrange equationsen_HK
dc.subjectImage registrationen_HK
dc.titleImage registration in intra-oral radiographyen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailTsui, WK:wktsui@eee.hku.hken_HK
dc.identifier.authorityTsui, WK=rp00182en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/IEMBS.2005.1617158-
dc.identifier.pmid17282927en_HK
dc.identifier.scopuseid_2-s2.0-33846928750en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33846928750&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage3206en_HK
dc.identifier.epage3209en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridLeung, CC=36725507200en_HK
dc.identifier.scopusauthoridYiu, KL=53870810500en_HK
dc.identifier.scopusauthoridZee, KY=6603722366en_HK
dc.identifier.scopusauthoridTsui, WK=7005623168en_HK
dc.identifier.issnl0589-1019-

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