Automated medical image registration using the simulated annealing algorithm

Maglogiannis, I; Zafiropoulos, E

dc.contributor.author	Maglogiannis, I	en
dc.contributor.author	Zafiropoulos, E	en
dc.date.accessioned	2014-03-01T02:42:30Z
dc.date.available	2014-03-01T02:42:30Z
dc.date.issued	2004	en
dc.identifier.issn	0302-9743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31024
dc.subject	Correlation Coefficient	en
dc.subject	Image Alignment	en
dc.subject	Medical Image	en
dc.subject	Optimal Solution	en
dc.subject	Optimization Problem	en
dc.subject	Simulated Annealing Algorithm	en
dc.subject	Ultrasound	en
dc.subject	X Rays	en
dc.subject.classification	Computer Science, Theory & Methods	en
dc.subject.other	Correlation coefficient	en
dc.subject.other	Image registration	en
dc.subject.other	Optimal solutions	en
dc.subject.other	Simulated annealing algorithms	en
dc.subject.other	Algorithms	en
dc.subject.other	Automation	en
dc.subject.other	Dermatology	en
dc.subject.other	Image analysis	en
dc.subject.other	Image communication systems	en
dc.subject.other	Optimization	en
dc.subject.other	Simulated annealing	en
dc.subject.other	Ultrasonic applications	en
dc.subject.other	Medical imaging	en
dc.title	Automated medical image registration using the simulated annealing algorithm	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-540-24674-9_48	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-540-24674-9_48	en
heal.language	English	en
heal.publicationDate	2004	en
heal.abstract	This paper presents a robust, automated registration algorithm, which may be applied to several types of medical images, including CTs, MRIs, X-rays, Ultrasounds and dermatological images. The proposed algorithm is intended for imaging modalities depicting primarily morphology of objects i.e. tumors, bones, cysts and lesions that are characterized by translation, scaling and rotation. An efficient deterministic algorithm is used in order to decouple these effects by transforming images into the log-polar Fourier domain. Then, the correlation coefficient function criterion is employed and the corresponding values of scaling and rotation are detected. Due to the non-linearity of the correlation coefficient function criterion and the heavy computational effort required for its full enumeration, this optimization problem is solved using an efficient simulated annealing algorithm. After the images alignment in scaling and rotation, the simulated annealing algorithm is employed again, in order to detect the remaining values of the horizontal and vertical shifting. The proposed algorithm was tested using different initialization schemes and resulted in fast convergence to the optimal solutions independently of the initial points.	en
heal.publisher	SPRINGER-VERLAG BERLIN	en
heal.journalName	Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)	en
heal.bookName	LECTURE NOTES IN COMPUTER SCIENCE	en
dc.identifier.doi	10.1007/978-3-540-24674-9_48	en
dc.identifier.isi	ISI:000221610800048	en
dc.identifier.volume	3025	en
dc.identifier.spage	456	en
dc.identifier.epage	465	en