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dc.contributor.authorBergmann, Ørjaneng
dc.contributor.authorKindlmann, Gordoneng
dc.contributor.authorPeled, Sharoneng
dc.contributor.authorWestin, Carl-Fredrikeng
dc.date.accessioned2008-10-16T12:33:41Z
dc.date.available2008-10-16T12:33:41Z
dc.date.issued2007eng
dc.PublishedBiomedical Imaging: From Nano to Macro, 2007. 4th IEEE International Symposium on 2007: 796 –799.en
dc.identifier.isbn1-4244-0672-2en_US
dc.identifier.urihttps://hdl.handle.net/1956/2800
dc.description.abstractEstimating white matter fiber pathways from a diffusion tensor MRI dataset has many important applications in medical research. However, the standard approach of performing tracking on single-tensor estimates per voxel is confounded by regions of multiple pathways in different directions. Building on previous work for estimating multiple tensors from MR value partitioning, we present here a two-tensor fiber tractography method that estimates two tensors from the acquired MR values, interpolated at each step of the path, and follows the tensor most aligned with the current direction. The method is verified on a synthetic dataset and applied to two locations of fiber crossing in an in vivo diffusion MRIen_US
dc.language.isoengeng
dc.publisherIEEEen_US
dc.subjectBiodiffusioneng
dc.subjectBiomedical MRIeng
dc.subjectBraineng
dc.subjectMedical image processingeng
dc.subjectNeurophysiologyeng
dc.subjectTensorseng
dc.subjectTrackingeng
dc.subjectMR value partitioningeng
dc.subjectDiffusion tensoreng
dc.subjectFiber crossingeng
dc.subjectIn vivo diffusion MRIeng
dc.subjectMagneticeng
dc.subjectResonance imagingeng
dc.subjectMedical researcheng
dc.subjectMultiple tensorseng
dc.subjectSingle-tensor estimateseng
dc.subjectTracking two-tensor fiber tractographyeng
dc.subjectWhite matter fiber pathwayseng
dc.titleTwo-tensor Fiber Tractographyen_US
dc.typePeer reviewed
dc.typeJournal article
dc.identifier.doihttps://doi.org/10.1109/isbi.2007.356972
dc.subject.nsiVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420nob


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