Robust fiber tracking method by vector selection criterion in diffusion tensor images

Keun Ho Kim, Itamar Ronen, Elia Formisano, Rainer Goebel, Kamil Ugurbil, Dae Shik Kim

Research output: Contribution to journalConference article

11 Scopus citations

Abstract

One of the most important applications of diffusion tensor image (DTI) is the in-vivo investigation of brain white-matter connectivity. However, DTI has difficulties on the reconstruction of axonal fibers. The data that is used to reconstruct the fibers is affected by partial volume effect, particularly at the border between gray and white matter, and the typical voxel size used in the acquisition of the MR images is larger than the characteristic size of the axonal fiber. The proposed vector criterion tracking method uses selective eigenvector interpolation for fiber tracking. As a result, the method produces faster and more stable trajectories with reducing memory consumption, compared to other current methods.

Original languageEnglish (US)
Pages (from-to)1080-1083
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume26 II
StatePublished - Dec 1 2004
EventConference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 - San Francisco, CA, United States
Duration: Sep 1 2004Sep 5 2004

Keywords

  • Connectivity
  • Diffusion tensor imaging
  • Fiber tracking
  • Partial volume effect

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