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A Novel Criterion for Characterizing Diffusion Anisotropy in HARDI Data Based on the MDL Technique

机译:基于MDL技术的HARDI数据扩散各向异性特征判据。

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摘要

Based on the spherical harmonic decomposition of HARDI data, we propose a new criterion for characterizing the diffusion anisotropy in a voxel directly from the SH coefficients. Essentially, by considering the Rician noise in diffusion data, we modify the Rissanen's criterion for fitting the diffusion situation in a voxel. In addition, the minimum description length (MDL) criterion has been employed for interpreting information from both the SH coefficients and the data. The criterion obtained can make use of the diffusion information so as to efficiently separate the different diffusion distributions. Various synthetic datasets have been used for verifying our method. The experimental results show the performance of the proposed criterion is accurate.
机译:基于HARDI数据的球谐分解,我们提出了一个直接根据SH系数表征体素中扩散各向异性的新准则。本质上,通过考虑扩散数据中的Rician噪声,我们修改了Rissanen准则以适合体素中的扩散情况。此外,最小描述长度(MDL)准则已用于从SH系数和数据中解释信息。所获得的标准可以利用扩散信息,以便有效地分离不同的扩散分布。各种综合数据集已用于验证我们的方法。实验结果表明,所提出准则的性能是准确的。

著录项

  • 来源
    《Medical biometrics》|2010年|p.413-422|共10页
  • 会议地点 Hong Kong(CN);Hong Kong(CN)
  • 作者单位

    Intelligent Systems Research Centre, University of Ulster at Magee Derry, BT48 7JL, Northern Ireland, UK;

    Intelligent Systems Research Centre, University of Ulster at Magee Derry, BT48 7JL, Northern Ireland, UK;

    Intelligent Systems Research Centre, University of Ulster at Magee Derry, BT48 7JL, Northern Ireland, UK;

    Intelligent Systems Research Centre, University of Ulster at Magee Derry, BT48 7JL, Northern Ireland, UK;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 生物医学工程;
  • 关键词

    hardi; spherical harmonic; mdl; diffusion anisotropy;

    机译:哈迪球谐mdl;扩散各向异性;

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