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dc.contributor.authorRehman, Tauseef ur
dc.contributor.authorTannenbaum, Allen R.
dc.date.accessioned2009-06-24T17:02:43Z
dc.date.available2009-06-24T17:02:43Z
dc.date.issued2007-01-29
dc.identifier.citationTauseef ur Rehman and Allen Tannenbaum, "Multigrid Optimal Mass Transport for Image Registration and Morphing," Computational Imaging V, Charles A. Bouman, Eric L. Miller, Ilya Pollak, Editors, Proc. of SPIE-IS&T Electronic Imaging, SPIE Vol. 6498, 649810, (2007)en
dc.identifier.issn0277-786X
dc.identifier.urihttp://hdl.handle.net/1853/28603
dc.description©2007 SPIE--The International Society for Optical Engineering. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. The electronic version of this article is the complete one and can be found online at: DOI Link: http://dx.doi.org/10.1117/12.702596en
dc.descriptionPresented at Computational imaging V, 29-31 January, 2007, San Jose, California, USA.
dc.descriptionDOI:10.1117/12.702596
dc.description.abstractIn this paper we present a computationally efficient Optimal Mass Transport algorithm. This method is based on the Monge-Kantorovich theory and is used for computing elastic registration and warping maps in image registration and morphing applications. This is a parameter free method which utilizes all of the grayscale data in an image pair in a symmetric fashion. No landmarks need to be specified for correspondence. In our work, we demonstrate significant improvement in computation time when our algorithm is applied as compared to the originally proposed method by Haker et al [1]. The original algorithm was based on a gradient descent method for removing the curl from an initial mass preserving map regarded as 2D vector field. This involves inverting the Laplacian in each iteration which is now computed using full multigrid technique resulting in an improvement in computational time by a factor of two. Greater improvement is achieved by decimating the curl in a multi-resolutional framework. The algorithm was applied to 2D short axis cardiac MRI images and brain MRI images for testing and comparison.en
dc.language.isoen_USen
dc.publisherGeorgia Institute of Technologyen
dc.subjectOptimal transporten
dc.subjectElastic registrationen
dc.subjectMass preservationen
dc.subjectMultigriden
dc.subjectMulti-resolutionen
dc.titleMultigrid optimal mass transport for image registration and morphingen
dc.typeProceedingsen
dc.contributor.corporatenameGeorgia Institute of Technology. Dept. of Biomedical Engineering
dc.contributor.corporatenameEmory University. Dept. of Biomedical Engineering
dc.contributor.corporatenameGeorgia Institute of Technology. School of Electrical and Computer Engineering
dc.publisher.originalSociety of Photo-Optical Instrumentation Engineers


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