Literature DB >> 24177264

AGREEMENT BETWEEN THE WHITE MATTER CONNECTIVITY BASED ON THE TENSOR-BASED MORPHOMETRY AND THE VOLUMETRIC WHITE MATTER PARCELLATIONS BASED ON DIFFUSION TENSOR IMAGING.

Seung-Goo Kim1, Hyekyoung Lee, Moo K Chung, Jamie L Hanson, Brian B Avants, James C Gee, Richard J Davidson, Seth D Pollak.   

Abstract

We are interested in investigating white matter connectivity using a novel computational framework that does not use diffusion tensor imaging (DTI) but only uses T1-weighted magnetic resonance imaging. The proposed method relies on correlating Jacobian determinants across different voxels based on the tensor-based morphometry (TBM) framework. In this paper, we show agreement between the TBM-based white matter connectivity and the DTI-based white matter atlas. As an application, altered white matter connectivity in a clinical population is determined.

Entities:  

Keywords:  brain network; structural connectivity; tensor-based morphometry; white matter atlas

Year:  2012        PMID: 24177264      PMCID: PMC3811041          DOI: 10.1109/ISBI.2012.6235479

Source DB:  PubMed          Journal:  Proc IEEE Int Symp Biomed Imaging        ISSN: 1945-7928


  8 in total

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2.  Comparing functional connectivity via thresholding correlations and singular value decomposition.

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4.  Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template.

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5.  Structural insights into aberrant topological patterns of large-scale cortical networks in Alzheimer's disease.

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6.  STRUCTURAL CONNECTIVITY VIA THE TENSOR-BASED MORPHOMETRY.

Authors:  Seung-Goo Kim; Moo K Chung; Jamie L Hanson; Brian B Avants; James C Gee; Richard J Davidson; Seth D Pollak
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2011

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Journal:  Psychiatry Clin Neurosci       Date:  2009-02       Impact factor: 5.188

  8 in total
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  2 in total

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