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Information Journal Paper

Title

HIGH ANGULAR RESOLUTION DIFFUSION IMAGE REGISTRATION

Pages

  1-9

Keywords

HIGH ANGULAR RESOLUTION DIFFUSION IMAGING (HARDI) 
Q 
ORIENTATION DISTRIBUTION FUNCTION (ODF) 
PRINCIPAL DIFFUSION DIRECTION (PDD) 

Abstract

 Diffusion Tensor Imaging (DTI) is a common method for the investigation of brain white matter. In this method, it is assumed that diffusion of water molecules is Gaussian and so, it fails in fiber crossings where this assumption does not hold. High Angular Resolution Diffusion Imaging (HARDI) allows more accurate investigation of microstructures of the brain white matter; it can present fiber crossing in each voxel. HARDI contains complex orientation information of the fibers.Therefore, REGISTRATION of these images is more complicated than the scalar images. In this paper, we propose a HARDI REGISTRATION algorithm based on the feature vectors that are extracted from the Orientation Distribution Functions (ODFs) in each voxel. Hammer similarity measure is used to match the feature vectors and thin-plate spline (TPS) based REGISTRATION is used for spatial REGISTRATION of the skeleton and its neighbors. A re-orientation strategy is utilized to re-orient the ODFs after spatial REGISTRATION. Finally, we evaluate our method based on the differences in principal diffusion direction and we will show that utilizing the skeleton as landmark in the REGISTRATION results in accurate alignment of HARDI data.

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    APA: Copy

    AFZALI, MARYAM, FATEMIZADEH, EMAD, & SOLTANIAN ZADEH, HAMID. (2015). HIGH ANGULAR RESOLUTION DIFFUSION IMAGE REGISTRATION. MACHINE VISION AND IMAGE PROCESSING, 2(1 ), 1-9. SID. https://sid.ir/paper/265710/en

    Vancouver: Copy

    AFZALI MARYAM, FATEMIZADEH EMAD, SOLTANIAN ZADEH HAMID. HIGH ANGULAR RESOLUTION DIFFUSION IMAGE REGISTRATION. MACHINE VISION AND IMAGE PROCESSING[Internet]. 2015;2(1 ):1-9. Available from: https://sid.ir/paper/265710/en

    IEEE: Copy

    MARYAM AFZALI, EMAD FATEMIZADEH, and HAMID SOLTANIAN ZADEH, “HIGH ANGULAR RESOLUTION DIFFUSION IMAGE REGISTRATION,” MACHINE VISION AND IMAGE PROCESSING, vol. 2, no. 1 , pp. 1–9, 2015, [Online]. Available: https://sid.ir/paper/265710/en

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