Show simple item record

dc.contributor.authorMalcolm, James G.
dc.contributor.authorMichailovich, Oleg
dc.contributor.authorBouix, Sylvain
dc.contributor.authorWestin, Carl-Fredrik
dc.contributor.authorShenton, Martha Elizabeth
dc.contributor.authorRathi, Yogesh
dc.date.accessioned2016-09-23T15:54:01Z
dc.date.issued2010
dc.identifier.citationMalcolm, James G., Oleg Michailovich, Sylvain Bouix, Carl-Fredrik Westin, Martha E. Shenton, and Yogesh Rathi. 2010. A Filtered Approach to Neural Tractography Using the Watson Directional Function. Medical Image Analysis 14, no. 1: 58–69. doi:10.1016/j.media.2009.10.003.en_US
dc.identifier.issn1361-8415en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:28549003
dc.description.abstractWe propose a technique to simultaneously estimate the local fiber orientations and perform multifiber tractography. Existing techniques estimate the local fiber orientation at each voxel independently so there is no running knowledge of confidence in the measured signal or estimated fiber orientation. Further, to overcome noise, many algorithms use a filter as a post-processing step to obtain a smooth trajectory. We formulate fiber tracking as causal estimation: at each step of tracing the fiber, the current estimate of the signal is guided by the previous. To do this, we model the signal as a discrete mixture of Watson directional functions and perform tractography within a filtering framework. Starting from a seed point, each fiber is traced to its termination using an unscented Kalman filter to simultaneously fit the signal and propagate in the most consistent direction. Despite the presence of noise and uncertainty, this provides an accurate estimate of the local structure at each point along the fiber. We choose the Watson function since it provides a compact representation of the signal parameterized by the principal diffusion direction and a scaling parameter describing anisotropy, and also allows analytic reconstruction of the oriented diffusion function from those parameters. Using a mixture of two and three components (corresponding to two-fiber and three-fiber models) we demonstrate in synthetic experiments that this approach reduces signal reconstruction error and significantly improves the angular resolution at crossings and branchings. In vivo experiments examine the corpus callosum and internal capsule and confirm the ability to trace through regions known to contain such crossing and branching while providing inherent path regularization.en_US
dc.language.isoen_USen_US
dc.publisherElsevier BVen_US
dc.relation.isversionofdoi:10.1016/j.media.2009.10.003en_US
dc.relation.hasversionhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3967593/en_US
dash.licenseLAA
dc.subjectDiffusion-weighted MRIen_US
dc.subjecttractographyen_US
dc.subjectKalman filteringen_US
dc.subjectWatson directional functionen_US
dc.titleA filtered approach to neural tractography using the Watson directional functionen_US
dc.typeJournal Articleen_US
dc.description.versionAccepted Manuscripten_US
dc.relation.journalMedical Image Analysisen_US
dash.depositing.authorShenton, Martha Elizabeth
dc.date.available2016-09-23T15:54:01Z
dc.identifier.doi10.1016/j.media.2009.10.003*
dash.identifier.orcid0000-0003-4235-7879en_US
dash.contributor.affiliatedWestin, Carl-Fredrik
dash.contributor.affiliatedRathi, Yogesh
dash.contributor.affiliatedBouix, Sylvain
dash.contributor.affiliatedShenton, Martha


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record