Detecting Structure in Diffusion Tensor MR Images

  • K. Krishna Nand
  • Rafeef Abugharbieh
  • Brian G. Booth
  • Ghassan Hamarneh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6892)


We derive herein first and second-order differential operators for detecting structure in diffusion tensor MRI (DTI). Unlike existing methods, we are able to generate full first and second-order differentials without dimensionality reduction and while respecting the underlying manifold of the data. Further, we extend corner and curvature feature detectors to DTI using our differential operators. Results using the feature detectors on diffusion tensor MR images show the ability to highlight structure within the image that existing methods cannot.


Differential Operator Fractional Anisotropy Diffusion Tensor Image Diffusion Tensor Hessian Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • K. Krishna Nand
    • 1
  • Rafeef Abugharbieh
    • 1
  • Brian G. Booth
    • 2
  • Ghassan Hamarneh
    • 2
  1. 1.Biomedical Signal and Image Computing LabUniversity of British ColumbiaCanada
  2. 2.Medical Image Analysis Lab, School of Computing ScienceSimon Fraser UniversityCanada

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