dc.contributor.author |
Matsopoulos, GK |
en |
dc.contributor.author |
Asvestas, PA |
en |
dc.contributor.author |
Mouravliansky, NA |
en |
dc.contributor.author |
Delibasis, KK |
en |
dc.date.accessioned |
2014-03-01T01:21:06Z |
|
dc.date.available |
2014-03-01T01:21:06Z |
|
dc.date.issued |
2004 |
en |
dc.identifier.issn |
0278-0062 |
en |
dc.identifier.uri |
https://dspace.lib.ntua.gr/xmlui/handle/123456789/16064 |
|
dc.subject |
Multimodal image registration |
en |
dc.subject |
Ophthalmology |
en |
dc.subject |
Retina |
en |
dc.subject |
Self organizing maps |
en |
dc.subject.classification |
Computer Science, Interdisciplinary Applications |
en |
dc.subject.classification |
Engineering, Biomedical |
en |
dc.subject.classification |
Engineering, Electrical & Electronic |
en |
dc.subject.classification |
Imaging Science & Photographic Technology |
en |
dc.subject.classification |
Radiology, Nuclear Medicine & Medical Imaging |
en |
dc.subject.other |
Angiography |
en |
dc.subject.other |
Bifurcation (mathematics) |
en |
dc.subject.other |
Blood vessels |
en |
dc.subject.other |
Cameras |
en |
dc.subject.other |
Charge coupled devices |
en |
dc.subject.other |
Image segmentation |
en |
dc.subject.other |
Multimedia systems |
en |
dc.subject.other |
Ophthalmology |
en |
dc.subject.other |
Self organizing maps |
en |
dc.subject.other |
Simulated annealing |
en |
dc.subject.other |
Choroid circulation |
en |
dc.subject.other |
Human-interactive registration |
en |
dc.subject.other |
Multimodal image registration |
en |
dc.subject.other |
Retina |
en |
dc.subject.other |
Medical imaging |
en |
dc.title |
Multimodal registration of retinal images using self organizing maps |
en |
heal.type |
journalArticle |
en |
heal.identifier.primary |
10.1109/TMI.2004.836547 |
en |
heal.identifier.secondary |
http://dx.doi.org/10.1109/TMI.2004.836547 |
en |
heal.language |
English |
en |
heal.publicationDate |
2004 |
en |
heal.abstract |
In this paper, an automatic method for registering multimodal retinal images is presented. The method consists of three steps: the vessel centerline detection and extraction of bifurcation points only in the reference image, the automatic correspondence of bifurcation points in the two images using a novel implementation of the self organizing maps and the extraction of the parameters of the affine transform using the previously obtained correspondences. The proposed registration algorithm was tested on 24 multimodal retinal pairs and the obtained results show an advantageous performance in terms of accuracy with respect to the manual registration. |
en |
heal.publisher |
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
en |
heal.journalName |
IEEE Transactions on Medical Imaging |
en |
dc.identifier.doi |
10.1109/TMI.2004.836547 |
en |
dc.identifier.isi |
ISI:000225453100009 |
en |
dc.identifier.volume |
23 |
en |
dc.identifier.issue |
12 |
en |
dc.identifier.spage |
1557 |
en |
dc.identifier.epage |
1562 |
en |