Pollari Mika, Neuvonen Tuomas, Lötjönen Jyrki
Laboratory of Biomedical Engineering, Helsinki University of Technology, FIN-02015 HUT, Finland.
Med Image Comput Comput Assist Interv. 2006;9(Pt 2):629-36. doi: 10.1007/11866763_77.
We present a new algorithm for affine registration of diffusion tensor magnetic resonance (DT-MR) images. The method is based on a new formulation of a point-wise tensor similarity measure, which weights directional and magnitude information differently depending on the type of diffusion. The method is compared to a reference method, which uses normalized mutual information (NMI), calculated either from a fractional anisotropy (FA) map or a T2-weighted MR image. The registration methods are applied to real and simulated DT-MR images. Visual assessment is done for real data and for simulated data, registration accuracy is defined. The results show that the proposed method outperforms the reference method.
我们提出了一种用于扩散张量磁共振（DT-MR）图像仿射配准的新算法。该方法基于一种新的逐点张量相似性度量公式，该公式根据扩散类型对方向和幅度信息赋予不同权重。将该方法与一种参考方法进行比较，该参考方法使用从分数各向异性（FA）图或T2加权MR图像计算得到的归一化互信息（NMI）。将配准方法应用于真实和模拟的DT-MR图像。对真实数据和模拟数据进行视觉评估，并定义配准精度。结果表明，所提出的方法优于参考方法。
