Show simple item record

dc.contributor.authorO'Donnell, Lauren Jean
dc.contributor.authorRigolo, Laura
dc.contributor.authorNorton, Isaiah
dc.contributor.authorWells, William Mercer
dc.contributor.authorWestin, Carl-Fredrik
dc.contributor.authorGolby, Alexandra Jacqueline
dc.date.accessioned2017-10-10T15:00:14Z
dc.date.issued2012
dc.identifierQuick submit: 2013-11-15T11:52:54-05:00
dc.identifier.citationO’Donnell, Lauren J., Laura Rigolo, Isaiah Norton, William M. Wells, Carl-Fredrik Westin, and Alexandra J. Golby. 2012. “fMRI-DTI Modeling via Landmark Distance Atlases for Prediction and Detection of Fiber Tracts.” NeuroImage 60 (1) (March): 456–470. doi:10.1016/j.neuroimage.2011.11.014.en_US
dc.identifier.issn1053-8119en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:34181703
dc.description.abstractThe overall goal of this research is the design of statistical atlas models that can be created from normal subjects, but may generalize to be applicable to abnormal brains. We present a new style of joint modeling of fMRI, DTI, and structural MRI. Motivated by the fact that a white matter tract and related cortical areas are likely to displace together in the presence of a mass lesion (brain tumor), in this work we propose a rotation and translation invariant model that represents the spatial relationship between fiber tracts and anatomic and functional landmarks. This landmark distance model provides a new basis for representation of fiber tracts and can be used for detection and prediction of fiber tracts based on landmarks. Our results indicate that the measured model is consistent across normal subjects, and thus suitable for atlas building. Our experiments demonstrate that the model is robust to displacement and missing data, and can be successfully applied to a small group of patients with mass lesions.en_US
dc.language.isoen_USen_US
dc.publisherElsevier BVen_US
dc.relation.isversionofdoi:10.1016/j.neuroimage.2011.11.014en_US
dc.relation.hasversionhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3423975/en_US
dash.licenseLAA
dc.subjectDiffusion MRI; Functional MRI; Atlas; White matter; Neuroimaging; Structure–functionen_US
dc.titlefMRI-DTI modeling via landmark distance atlases for prediction and detection of fiber tractsen_US
dc.typeJournal Articleen_US
dc.date.updated2013-11-15T16:54:05Z
dc.description.versionAccepted Manuscripten_US
dc.rights.holderO'Donnell LJ, Rigolo L, Norton I, Wells WM 3rd, Westin CF, Golby AJ
dc.relation.journalNeuroImageen_US
dash.depositing.authorGolby, Alexandra Jacqueline
dc.date.available2017-10-10T15:00:14Z
dc.identifier.doi10.1016/j.neuroimage.2011.11.014*
workflow.legacycommentsaa.no Golby emailed for aa 04-25-2017 MMen_US
dash.authorsorderedfalse
dash.contributor.affiliatedWestin, Carl-Fredrik
dash.contributor.affiliatedO'Donnell, Lauren
dash.contributor.affiliatedGolby, Alexandra
dash.contributor.affiliatedWells, William


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record