Advanced MR diffusion characterization of neural tissue using directional diffusion kurtosis analysis

Edward S. Hui, Matthew M. Cheung, Liqun Qi, Ed X. Wu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

29 Citations (Scopus)

Abstract

MR Diffusion kurtosis imaging (DKI) was proposed recently to study the deviation of water diffusion from Gaussian distribution. Mean kurtosis (MK), directionally averaged kurtosis, has been shown to be useful in assessing pathophysilogical changes. However, MK is not sensitive to kurtosis change occurring along a specific direction. Therefore, orthogonal transformation of the 4 th order kurtosis tensor was introduced in the current study to compute kurtoses along the 3 eigenvector directions of the 2 nd order diffusion tensor. Such axial (K ||) and radial (K- ⊥) kurtoses measured the kurtoses along the directions parallel and perpendicular, respectively, to the principal diffusion direction. DKI experiments were performed in normal adult and formalin-fixed rat brain, and developmental brains. The results showed that directional kurtosis analysis revealed different information for tissue characterization.
Original languageEnglish
Title of host publicationProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Pages3941-3944
Number of pages4
Publication statusPublished - 1 Dec 2008
Event30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada
Duration: 20 Aug 200825 Aug 2008

Conference

Conference30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Country/TerritoryCanada
CityVancouver, BC
Period20/08/0825/08/08

Keywords

  • And orthogonal transformation
  • Diffusion kurtosis tensor
  • Directional kurtosis
  • Restricted diffusion

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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