A New Registration Algorithm Combined MRF with BBR

Junyi Yan, Jinzhu Yang
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Abstract

This paper proposes a registration algorithm which combined MRF and BBR. First, this approach uses MRF to segment the reference volume, then, it extracts the boundary of brain white matter from the segmented volume and takes the intensities of points across the boundary of white matter as the similarity of egistration. Compared with other algorithms based boundary, it merely need to extract the boundary of white matter in reference volume. Through comparing with other algorithms based CR and NMI, we can get the onclusion that it can run faster and can achieve comparable accuracy and good robust.
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一种结合MRF和BBR的配准新算法
本文提出了一种MRF和BBR相结合的配准算法。该方法首先利用磁共振成像(MRF)对参考体积进行分割,然后从分割的体积中提取脑白质边界,并以脑白质边界上点的强度作为配准相似度。与其他基于边界的算法相比,该算法只需要提取参考体积中的白质边界即可。通过与其他基于CR和NMI的算法的比较,得出该算法运行速度更快,具有相当的精度和良好的鲁棒性的结论。
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