CT-MRI automatic surface-based registration schemes combining global and local optimization techniques

dc.contributor.author	Ματσόπουλος, Γεώργιος Κ.	el
dc.contributor.author	Δελήμπασης, Κωνσταντίνος Κ.	el
dc.contributor.author	Μουραβλιάνσκυ, Νικόλαος Α.	el
dc.contributor.author	Ασβεστάς, Παντελής Α.	el
dc.contributor.author	Νικήτα, Κωνσταντίνα Σ.	el
dc.date.accessioned	2015-01-13T15:42:07Z
dc.date.issued	2015-01-13
dc.identifier.uri	http://hdl.handle.net/11400/3939
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.subject	Medical image registration
dc.subject	Clinical environment
dc.subject	Ιατρική εικόνα
dc.subject	Κλινικό περιβάλλον
dc.title	CT-MRI automatic surface-based registration schemes combining global and local optimization techniques	en
heal.type	journalArticle
heal.classification	Medicine
heal.classification	Medical technology
heal.classification	Ιατρική
heal.classification	Ιατρικά όργανα και εξοπλισμός
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh00006614
heal.classificationURI	http://skos.um.es/unescothes/C02465
heal.classificationURI	N/A-Ιατρική
heal.classificationURI	N/A-Ιατρικά όργανα και εξοπλισμός
heal.contributorName	Κουλουλιάς, Βασίλειος Ε.	el
heal.contributorName	Ουζούνογλου, Νικόλαος Κ.	el
heal.dateAvailable	10000-01-01
heal.language	en
heal.access	forever
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.	el
heal.publicationDate	2003
heal.bibliographicCitation	Matsopoulos, K., Delibasis, K., Mouravliansky, N., Asvestas, P., Nikita, K., et al. (2003). CT-MRI automatic surface-based registration schemes combining global and local optimization techniques. Technology and Health Care. 11(4). pp. 219-232. IOS Press.	en
heal.abstract	Medical image registration is commonly required in order to combine the complementary information provided by different medical imaging modalities. In this paper, a new automatic registration scheme is proposed to register 3-D CT-MR head images and is currently tested on a clinical environment. The proposed scheme, after the preprocessing and the outer surface extraction of the data, is based on the use the rigid transformation method, in conjunction with a combination of global and local optimization techniques. Analytically, the paper exploits the optimization efficiency of three widely used optimization techniques, in obtaining the parameters of the rigid transformation model: the Downhill Simplex Method, the Genetic Algorithms and the Simulated Annealing. These optimization techniques are further combined by the sequential application of the Powell optimization method in order to refine the registration and increase its accuracy. A comparative study involving these optimization techniques in conjunction with the rigid transformation, and two other methods, the ICP and the manual methods, is also presented, for a sufficient number of clinical CT-MR brain images. Finally, quantitative and qualitative results are also presented to validate the performance of these automatic surface-based registration schemes, in terms of consistency and accuracy. Throughout of this study, the automatic registration scheme comprising of the rigid transformation in conjunction with the Simulated Annealing method sequentially combined with the Powell method has been performed superior regarding all the other compared registration schemes.	en
heal.publisher	IOS Press	en
heal.journalName	Technology and Health Care	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true