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Automated probabilistic reconstruction of white-matter pathways in health and disease using an atlas of the underlying anatomy.

Frontiers in neuroinformatics | 2011

We have developed a method for automated probabilistic reconstruction of a set of major white-matter pathways from diffusion-weighted MR images. Our method is called TRACULA (TRActs Constrained by UnderLying Anatomy) and utilizes prior information on the anatomy of the pathways from a set of training subjects. By incorporating this prior knowledge in the reconstruction procedure, our method obviates the need for manual interaction with the tract solutions at a later stage and thus facilitates the application of tractography to large studies. In this paper we illustrate the application of the method on data from a schizophrenia study and investigate whether the inclusion of both patients and healthy subjects in the training set affects our ability to reconstruct the pathways reliably. We show that, since our method does not constrain the exact spatial location or shape of the pathways but only their trajectory relative to the surrounding anatomical structures, a set a of healthy training subjects can be used to reconstruct the pathways accurately in patients as well as in controls.

Pubmed ID: 22016733 RIS Download

Research resources used in this publication

None found

Antibodies used in this publication

None found

Associated grants

  • Agency: NCRR NIH HHS, United States
    Id: S10 RR019307
  • Agency: NCRR NIH HHS, United States
    Id: P41 RR014075
  • Agency: NINDS NIH HHS, United States
    Id: R01 NS052585
  • Agency: NCCIH NIH HHS, United States
    Id: RC1 AT005728
  • Agency: NIMH NIH HHS, United States
    Id: U54 MH091657
  • Agency: Medical Research Council, United Kingdom
    Id: G0800578
  • Agency: NINDS NIH HHS, United States
    Id: R21 NS072652
  • Agency: NCRR NIH HHS, United States
    Id: S10 RR023043
  • Agency: NIBIB NIH HHS, United States
    Id: R00 EB008129
  • Agency: NIBIB NIH HHS, United States
    Id: R01 EB006758
  • Agency: NCRR NIH HHS, United States
    Id: S10 RR023401
  • Agency: NIA NIH HHS, United States
    Id: R01 AG022381
  • Agency: NCRR NIH HHS, United States
    Id: U24 RR021382
  • Agency: NIBIB NIH HHS, United States
    Id: K99 EB008129
  • Agency: NIMH NIH HHS, United States
    Id: U01 MH093765
  • Agency: NINDS NIH HHS, United States
    Id: R01 NS070963

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RRID:SCR_001847

Open source software suite for processing and analyzing human brain MRI images. Used for reconstruction of brain cortical surface from structural MRI data, and overlay of functional MRI data onto reconstructed surface. Contains automatic structural imaging stream for processing cross sectional and longitudinal data. Provides anatomical analysis tools, including: representation of cortical surface between white and gray matter, representation of the pial surface, segmentation of white matter from rest of brain, skull stripping, B1 bias field correction, nonlinear registration of cortical surface of individual with stereotaxic atlas, labeling of regions of cortical surface, statistical analysis of group morphometry differences, and labeling of subcortical brain structures.Operating System: Linux, macOS.

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RRID:SCR_002823

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TrackVis (tool)

RRID:SCR_004817

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Human Connectome Coordination Facility (tool)

RRID:SCR_008749

Consortium to comprehensively map long-distance brain connections and their variability. It is acquiring data and developing analysis pipelines for several modalities of neuroimaging data plus behavioral and genetic data from healthy adults.

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