DTI Image Registration under Probabilistic Fiber Bundles Tractography Learning.

Diffusion Tensor Imaging (DTI) image registration is an essential step for diffusion tensor image analysis. Most of the fiber bundle based registration algorithms use deterministic fiber tracking technique to get the white matter fiber bundles, which will be affected by the noise and volume. In orde...

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Publicado en:BioMed Research International Vol. 2016; pp. 1 - 13
Autores principales: Guo, Zhe, Wang, Yi, Lei, Tao, Fan, Yangyu, Zhang, Xiuwei
Formato: diagnostic images equations & formulas research tables/charts Journal Article
Publicado: Wiley-Blackwell 9/27/2016
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 9/27/2016
      vid: 2016
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2016/4674658
        118364778
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        atl: DTI Image Registration under Probabilistic Fiber Bundles Tractography Learning.
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        au:
          Guo, Zhe
          Wang, Yi
          Lei, Tao
          Fan, Yangyu
          Zhang, Xiuwei
        affil: School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China
      sug:
        subj:
          Magnetic Resonance Imaging Methods
          Probability
          Neural Pathways Analysis
          Models, Structural
          Brain Analysis
          Human
          Nerve Fibers Analysis
          Algorithms
          Random Sample
          Male
          Female
          Middle Age
          Adult
          Aged
          Descriptive Statistics
          Funding Source
          Middle Aged: 45-64 years
          Adult: 19-44 years
          Aged: 65+ years
          Male
          Female
      ab: Diffusion Tensor Imaging (DTI) image registration is an essential step for diffusion tensor image analysis. Most of the fiber bundle based registration algorithms use deterministic fiber tracking technique to get the white matter fiber bundles, which will be affected by the noise and volume. In order to overcome the above problem, we proposed a Diffusion Tensor Imaging image registration method under probabilistic fiber bundles tractography learning. Probabilistic tractography technique can more reasonably trace to the structure of the nerve fibers. The residual error estimation step in active sample selection learning is improved by modifying the residual error model using finite sample set. The calculated deformation field is then registered on the DTI images. The results of our proposed registration method are compared with 6 state-of-the-art DTI image registration methods under visualization and 3 quantitative evaluation standards. The experimental results show that our proposed method has a good comprehensive performance.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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