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We presented for the first time an atlas-based clustering framework for fiber tracts of the whole human brain

Automated atlas-based clustering of white matter fiber tracts from DTMRI.

MICCAI, no. Pt 1 (2005): 188-195

Cited by: 89|Views21
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Abstract

A new framework is presented for clustering fiber tracts into anatomically known bundles. This work is motivated by medical applications in which variation analysis of known bundles of fiber tracts in the human brain is desired. To include the anatomical knowledge in the clustering, we invoke an atlas of fiber tracts, labeled by the numbe...More

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Introduction
  • Diffusion tensor MR imaging (DT-MRI) non-invasively measures the diffusivity of water molecules within the tissue [1].
  • Limited work has been done to address the inter-subject similarity/variability of the fiber tracts in the human brain, which is the ultimate goal.
  • Toward this goal and to quantitatively analyze the fiber tracts in a population, the first step is to identify the fiber tract clusters in each case.
  • An alternative approach is to extract all of the tracts in the whole brain and automatically cluster the desired bundles
Highlights
  • Diffusion tensor MR imaging (DT-MRI) non-invasively measures the diffusivity of water molecules within the tissue [1]
  • While anisotropy measures are being used to assess the density of the fiber tracts and or the degree of myelination in different regions of the brain, tractography methods have been
  • We propose to use a labeled atlas of the fiber tracts of the whole brain to perform clustering on the subjects under study
  • We presented for the first time an atlas-based clustering framework for fiber tracts of the whole human brain
  • Preliminary results prove the efficiency of the proposed method to cluster the fiber tracts into anatomically known bundles
  • Since the atlas has a significant impact on the clustering results, modification and improvement of the atlas, in terms of accuracy of region of interests, and the inclusion of more cases when constructing the atlas are of great importance
Conclusion
  • The authors presented for the first time an atlas-based clustering framework for fiber tracts of the whole human brain.
  • Preliminary results prove the efficiency of the proposed method to cluster the fiber tracts into anatomically known bundles.
  • The proposed framework has the flexibility to use different similarity measures, such as spatial distance or shape similarity or a combination of them, for different structures.
  • Quantitative analysis and study of the variability of particular fiber tract bundles in a population is currently underway
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