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dc.contributor.authorRehman, Tauseef ur
dc.contributor.authorHaber, Eldad
dc.contributor.authorPohl, Kilian M.
dc.contributor.authorHaker, Steven
dc.contributor.authorHalle, Michael
dc.contributor.authorTalos, Florin
dc.contributor.authorWald, Lawrence L.
dc.contributor.authorKikinis, Ron
dc.contributor.authorTannenbaum, Allen R.
dc.date.accessioned2009-07-28T14:49:39Z
dc.date.available2009-07-28T14:49:39Z
dc.date.issued2008-09
dc.identifier.citationTauseef ur Rehman, Eldad Haber, Kilian M. Pohl, Steven Haker, Mike Halle, Florin Talos, Lawrence L. Wald, Ron Kikinis and Allen Tannenbaum, "Multimodal Registration of White Matter Brain Data via Optimal Mass Transport," The MIDAS Journal - Computational Biomechanics for Medicine (MICCAI 2008 Workshop) 27-36: http://hdl.handle.net/10380/1380en
dc.identifier.urihttp://hdl.handle.net/1853/29245
dc.description.abstractThe elastic registration of medical scans from different acquisition sequences is becoming an important topic for many research labs that would like to continue the post-processing of medical scans acquired via the new generation of high-field-strength scanners. In this note, we present a parameter-free registration algorithm that is well suited for this scenario as it requires no tuning to specific acquisition sequences. The algorithm encompasses a new numerical scheme for computing elastic registration maps based on the minimizing flow approach to optimal mass transport. The approach utilizes all of the gray-scale data in both images, and the optimal mapping from image A to image B is the inverse of the optimal mapping from B to A. Further, no landmarks need to be specified, and the minimizer of the distance functional involved is unique. We apply the algorithm to register the white matter folds of two different scans and use the results to parcellate the cortex of the target image. To the best of our knowledge, this is the first time that the optimal mass transport function has been applied to register large 3D multimodal data sets.en
dc.language.isoen_USen
dc.publisherGeorgia Institute of Technologyen
dc.subjectOptimal mass transporten
dc.subjectRegistrationen
dc.subjectMonge Kantorovichen
dc.subjectVariational methodsen
dc.subjectFluid mechanicsen
dc.titleMultimodal Registration of White Matter Brain Data via Optimal Mass Transporten
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.contributor.corporatenameEmory University. Dept. of Mathematics and Computer Science
dc.contributor.corporatenameBrigham and Women’s Hospital. Dept. of Radiology. Surgical Planning Laboratory
dc.contributor.corporatenameMassachusetts General Hospital. Dept. of Radiology
dc.publisher.originalInsight Software Consortium


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