• DocumentCode
    128652
  • Title

    A new model-based spherical deconvolution method for multi-fiber reconstruction

  • Author

    Wu Ye ; Xu Youyou ; Feng Yuanjing ; Gao Chengfeng ; Li Fei

  • Author_Institution
    Coll. of Inf. Eng., Zhejiang Univ. of Technol., Hangzhou, China
  • fYear
    2014
  • fDate
    9-11 June 2014
  • Firstpage
    1456
  • Lastpage
    1460
  • Abstract
    We propose a novel method to reconstruct the multi-fiber orientation in this work. Firstly, we convolve DW-MRI signal with response function which is model-based to get the discretized fiber orientation distribution function. Secondly, we used the centered spherical Gaussian functions and the discretized fiber orientation density function to form a continuous fiber orientation density function which can correctly reveal the true fiber orientation density distributions in the 3D space. Finally, the properties of the method are demonstrated using both simulations and real datasets. And the results demonstrated the superiority of the proposed method over several existing multi-fiber reconstruction methods.
  • Keywords
    Gaussian processes; biodiffusion; biomedical MRI; deconvolution; image reconstruction; medical image processing; 3D space; DW-MRI signal; centered spherical Gaussian functions; continuous fiber orientation density function; discretized fiber orientation density function; discretized fiber orientation distribution function; model-based spherical deconvolution method; multifiber orientation reconstruction; multifiber reconstruction method; response function; true fiber orientation density distributions; Deconvolution; Density functional theory; Diffusion tensor imaging; Image resolution; Standards; Tensile stress; Multi-fiber reconstruction; high angular resolution diffusion imaging (HARDI); spherical deconvolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications (ICIEA), 2014 IEEE 9th Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4799-4316-6
  • Type

    conf

  • DOI
    10.1109/ICIEA.2014.6931398
  • Filename
    6931398