An iterative point correspondence algorithm for automatic image registration

dc.contributor.author	Μαρκάκη, Βασιλική Ε.	el
dc.contributor.author	Ασβεστάς, Παντελής Α.	el
dc.contributor.author	Ματσόπουλος, Γεώργιος Κ.	el
dc.date.accessioned	2015-02-09T08:59:50Z
dc.date.available	2015-02-09T08:59:50Z
dc.date.issued	2015-02-09
dc.identifier.uri	http://hdl.handle.net/11400/5900
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://www.elsevier.com	en
dc.subject	Mutual information
dc.subject	Automatic point correspondence
dc.subject	Αμοιβαία ενημέρωση
dc.subject	Αυτόματο σημείο αλληλογραφίας
dc.title	An iterative point correspondence algorithm for automatic image registration	en
heal.type	journalArticle
heal.secondaryTitle	an application to dental subtraction radiography	en
heal.classification	Medicine
heal.classification	Biomedical engineering
heal.classification	Ιατρική
heal.classification	Βιοϊατρική τεχνολογία
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh00006614
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85014237
heal.classificationURI	N/A-Ιατρική
heal.classificationURI	N/A-Βιοϊατρική τεχνολογία
heal.identifier.secondary	doi:10.1016/j.cmpb.2008.07.003
heal.language	en
heal.access	campus
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.	el
heal.publicationDate	2009
heal.bibliographicCitation	Markaki, V., Asvestas, P. and Matsopoulos, G. (January 2009). An iterative point correspondence algorithm for automatic image registration: an application to dental subtraction radiography. Computer Methods and Programs in Biomedicine. 93(1). pp. 61-72. Elsevier Science Ltd. Available from: http://www.sciencedirect.com [Accessed 29/08/2008]	en
heal.abstract	In this paper, an Automatic Iterative Point Correspondence (AIPC) algorithm towards image registration is presented. Given an image pair, distinctive points are extracted only in one of the images (reference image), and the corresponding points in the other image are obtained automatically by maximizing a similarity measure between regions of the two images with respect to the parameters of a local transformation. The maximization is accomplished by means of an iterative procedure, in which candidate solutions for the transformation parameters are tested at each iteration; these solutions are evaluated by the similarity measure between image regions. The detected point pairs by the application of the AIPC algorithm are then used to estimate the parameters of a global projective transformation for the registration of the image pair. The proposed AIPC algorithm was applied on 113 in vitro and in vivo dental image pairs providing improved registration accuracy against three widely used registration methods.	en
heal.publisher	Elsevier Science Ltd	en
heal.journalName	Computer Methods and Programs in Biomedicine	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true