An iterative point correspondence algorithm for automatic image registration: An application to dental subtraction radiography

Markaki, VE; Asvestas, PA; Matsopoulos, GK

dc.contributor.author	Markaki, VE	en
dc.contributor.author	Asvestas, PA	en
dc.contributor.author	Matsopoulos, GK	en
dc.date.accessioned	2014-03-01T01:29:50Z
dc.date.available	2014-03-01T01:29:50Z
dc.date.issued	2009	en
dc.identifier.issn	0169-2607	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/19368
dc.subject	Automatic point correspondence	en
dc.subject	Dental subtraction radiography	en
dc.subject	Iterative Closest Point	en
dc.subject	Mutual information	en
dc.subject	Point-based registration	en
dc.subject	Template matching	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Computer Science, Theory & Methods	en
dc.subject.classification	Engineering, Biomedical	en
dc.subject.classification	Medical Informatics	en
dc.subject.other	Automatic point correspondence	en
dc.subject.other	Dental subtraction radiography	en
dc.subject.other	Iterative Closest Point	en
dc.subject.other	Mutual information	en
dc.subject.other	Point-based registration	en
dc.subject.other	Image enhancement	en
dc.subject.other	Image registration	en
dc.subject.other	Radiography	en
dc.subject.other	Radiology	en
dc.subject.other	Template matching	en
dc.subject.other	Image processing	en
dc.subject.other	Algorithms	en
dc.subject.other	Biometry	en
dc.subject.other	Dental Models	en
dc.subject.other	Humans	en
dc.subject.other	Radiographic Image Interpretation, Computer-Assisted	en
dc.subject.other	Radiography, Dental, Digital	en
dc.title	An iterative point correspondence algorithm for automatic image registration: An application to dental subtraction radiography	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.cmpb.2008.07.003	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.cmpb.2008.07.003	en
heal.language	English	en
heal.publicationDate	2009	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. (c) 2008 Elsevier Ireland Ltd. All rights reserved.	en
heal.publisher	ELSEVIER IRELAND LTD	en
heal.journalName	Computer Methods and Programs in Biomedicine	en
dc.identifier.doi	10.1016/j.cmpb.2008.07.003	en
dc.identifier.isi	ISI:000263214200006	en
dc.identifier.volume	93	en
dc.identifier.issue	1	en
dc.identifier.spage	61	en
dc.identifier.epage	72	en