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3D Gabor Wavelets for Evaluating Medical Image Registration Algorithms

机译:用于评估医学图像登记算法的3D Gabor小波

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A Gabor wavelets based method is proposed in this paper for evaluating and tuning the parameters of image registration algorithms. The registration quality is measured by the anatomical variability of the registered images. We propose in this paper a local anatomical structure descriptor, namely the Maximum Responded Gabor Wavelet (MRGW) for such a purpose. The effectiveness of the descriptor is demonstrated through a practical spatial normalization example - the variance of MRGW is successfully applied to tune the parameters of a nonlinear spatial normalization algorithm, which is integrated in one of the most popular software packages for medical image processing - the Statistical Parametric Mapping (SPM).
机译:本文提出了一种基于Gabor小波的方法,用于评估和调整图像配准算法的参数。通过注册图像的解剖变换来衡量登记质量。我们在本文中提出了局部解剖结构描述符,即用于这种目的的最大响应的Gabor小波(MRGW)。通过实际的空间归一化示例来证明描述符的有效性 - MRGW的方差成功应用于调整非线性空间归一化算法的参数,该算法集成在用于医学图像处理的最受欢迎的软件包之一 - 统计参数映射(SPM)。

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