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Canonical polyadic decomposition for principal diffusion direction extraction in diffusion weighted imaging

Afzali, M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/IranianCEE.2017.7985253
  3. Abstract:
  4. Diffusion weighted imaging is a non-invasive method for investigation of brain fiber bundles. In diffusion tensor imaging (DTI), the diffusion of water molecules is assumed Gaussian, therefore, it can just show a single fiber direction in a voxel. To overcome this limitation, a number of high angular resolution diffusion imaging methods have been proposed. One of these techniques is Q-ball imaging. Using this method, we can extract orientation distribution function (ODF) that shows the orientations of multiple fibers in a voxel. For extracting the fiber directions, the maxima of the ODFs are conventionally determined. However, the results of this approach are sensitive to noise. To improve the results, we present a method for extracting principal diffusion directions using a tensor decomposition method. The results obtained using simulated and real data show that our proposed method has a better performance compared to the local maxima. For SNRs less than 30 dB, the similarity value of our method is 0.3 larger than that of the local maxima method. © 2017 IEEE
  5. Keywords:
  6. DW-MRI ; Diffusion ; Distribution functions ; Fibers ; Magnetic resonance imaging ; Molecules ; Noninvasive medical procedures ; Tensors ; Canonical polyadic decompositions ; Diffusion direction ; Diffusion weighted imaging ; Fiber tracking ; High angular resolution diffusion imaging ; Orientation distribution function ; Q-ball imaging ; Tensor decomposition ; Diffusion tensor imaging
  7. Source: 2017 25th Iranian Conference on Electrical Engineering, ICEE 2017, 2 May 2017 through 4 May 2017 ; 2017 , Pages 122-127 ; 9781509059638 (ISBN)
  8. URL: https://ieeexplore.ieee.org/document/7985253