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Medical image registration based on feature and mutual information

机译:基于特征和互信息的医学图像配准

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Image registration based on mutual information (MI) has been widely used in remote sensing data analysis, computer vision, medical image disposal and other fields. But the mutual information is calculated by the joint histogram of two images which don't take into account the space-position relationship of the image pixel, so the registration precision will be degraded. Aiming at the lack of mutual information registration, a new method of medical image registration based on mutual information of multi-scale Harris corner and feature points was given. It effectively improves sensitivity of noise and the situation of being trapped into a local minimum to MI registration.
机译:基于互信息(MI)的图像配准已广泛应用于遥感数据分析,计算机视觉,医学图像处理等领域。但是,互信息是由两个图像的联合直方图计算的,而没有考虑图像像素的空间位置关系,因此配准精度会降低。针对缺乏互信息配准的问题,提出了一种基于多尺度Harris角点和特征点互信息的医学图像配准的新方法。它有效地提高了对噪声的敏感度,并提高了对MI注册陷入局部最小值的情况。

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