Impact of Filtering on Region of Interest Estimation from Diffusion Weighted Brain Images
Impact of Filtering on Region of Interest Estimation from Diffusion Weighted Brain Images
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DOI：
10.1515/bmt-2013-4287
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发表时间：
2013-09
期刊：
影响因子：
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通讯作者：
Helen Perkunder;G. Ivanova
中科院分区：
文献类型：
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作者：
Helen Perkunder;G. Ivanova
对于扩散加权成像数据，没有用于图像预处理的标准化流水线，特别是关于滤波器应用。在这里，我们展示了Perona Malik滤波器，自适应成像滤波器，对导出的纤维轨迹相对于其endvoxels的影响。这些末端体素是跟踪的重要结果，因为它们通常被视为进一步调查的感兴趣区域，即当组合多种调查方法时。初步研究结果表明，Perona Malik滤波器应用于皮质脊髓轨迹（即长上级/下级轨迹）在感兴趣区域估计方面没有明显优势。
For diffusion weighted imaging data there is no standardised pipeline for image preprocessing, especially in regard to filter application. Here, we demonstrate the impact of the Perona Malik Filter, an adaptive imaging filter, on derived fiber tracks with respect to their endvoxels. These end-voxels are an important outcome of tracking, for they are often taken as regions of interest for further investigations, i.e. when combining multiple investigation methods. The preliminary findings suggest that the application of the Perona Malik filter for corticospinal tracks (i.e. long superior/inferior tracks) has no distinct advantages with respect to region of interest estimation.