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

Matsopoulos, GK; Delibasis, KK; Mouravliansky, NA; Asvestas, PA; Nikita, KS; Kouloulias, VE; Uzunoglu, NK

dc.contributor.author	Matsopoulos, GK	en
dc.contributor.author	Delibasis, KK	en
dc.contributor.author	Mouravliansky, NA	en
dc.contributor.author	Asvestas, PA	en
dc.contributor.author	Nikita, KS	en
dc.contributor.author	Kouloulias, VE	en
dc.contributor.author	Uzunoglu, NK	en
dc.date.accessioned	2014-03-01T01:52:57Z
dc.date.available	2014-03-01T01:52:57Z
dc.date.issued	2003	en
dc.identifier.issn	09287329	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/26801
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0142125775&partnerID=40&md5=0dd0c1ad6ab01e9669eb02c6bdbc0e65	en
dc.subject.other	analytic method	en
dc.subject.other	article	en
dc.subject.other	automation	en
dc.subject.other	brain radiography	en
dc.subject.other	computer assisted tomography	en
dc.subject.other	genetic algorithm	en
dc.subject.other	human	en
dc.subject.other	information processing	en
dc.subject.other	intermethod comparison	en
dc.subject.other	nuclear magnetic resonance imaging	en
dc.subject.other	priority journal	en
dc.subject.other	qualitative analysis	en
dc.subject.other	quantitative analysis	en
dc.subject.other	registration	en
dc.subject.other	simulation	en
dc.subject.other	technique	en
dc.subject.other	validation process	en
dc.subject.other	Algorithms	en
dc.subject.other	Brain	en
dc.subject.other	Humans	en
dc.subject.other	Imaging, Three-Dimensional	en
dc.subject.other	Magnetic Resonance Imaging	en
dc.subject.other	Models, Biological	en
dc.subject.other	Tomography, X-Ray Computed	en
dc.title	CT-MRI automatic surface-based registration schemes combining global and local optimization techniques	en
heal.type	journalArticle	en
heal.publicationDate	2003	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.journalName	Technology and Health Care	en
dc.identifier.volume	11	en
dc.identifier.issue	4	en
dc.identifier.spage	219	en
dc.identifier.epage	232	en