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White matter lesion segmentation based on feature joint occurrence probability and χ~2 random field theory from magnetic resonance (MR) images

机译:基于特征关节出现概率和χ〜2随机场理论的磁共振图像白质病变分割

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摘要

Lesions of the brain's white matter are common findings in MR examinations of elderly subjects. A fully automatic method for segmenting white matter lesions is proposed here. The joint probability of multi-modality MR image intensities is used as a feature to segment lesions, because lesion intensities usually are outliers of the normal tissue intensities and the lesions' joint intensity probability appears much smaller than those of normal brain tissues. The χ~2 random field theory is used to determine the significance of a detected lesion and provides a strict statistical analysis to exclude small-sized false-positive lesions. Experimental results show that the automatic segmentation of lesions is in high agreement with manual segmentation, and the χ~2 random-field-based statistical analysis greatly improves lesion seg-rnmentation results.
机译:在老年受试者的MR检查中,大脑白质病变是常见的发现。在此提出一种用于分割白质病变的全自动方法。多模态MR图像强度的联合概率被用作分割病变的特征,因为病变强度通常是正常组织强度的异常值,并且病变的联合强度概率似乎比正常脑组织的概率小得多。 χ〜2随机场理论用于确定检测到的病变的重要性,并提供严格的统计分析以排除小型假阳性病变。实验结果表明,病变的自动分割与人工分割高度吻合,基于χ〜2随机域的统计分析大大提高了病变分割的效果。

著录项

  • 来源
    《Pattern recognition letters》 |2010年第9期|p.781-790|共10页
  • 作者单位

    Signal and Image Processing Lab, Department of Biomedical Engineering, University of California, Irvine, Irvine, CA 92697, United States;

    Division of Translational Imaging Research, Department of Radiological Sciences, St. Jude Children's Research Hospital, Memphis, TN 38105, USA;

    Signal and Image Processing Lab, Department of Biomedical Engineering, University of California, Irvine, Irvine, CA 92697, United States;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    white matter lesions; joint probability; χ~2 random field theory;

    机译:白质病变联合概率χ〜2随机场理论;

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