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Mutual information based image registration for MRI and CT SCAN brain images

机译:基于互信息的MRI和CT SCAN脑图像的图像配准

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Image registration is the process of transforming the different sets of data, which is acquired by sampling of the same scene or object at different times or from different perspectives, into one coordinate system. This paper presents an algorithm for recovering translation parameter from two images that differ by Rotation, Scaling, Transformation and Rotation-scale-Translation (RST) also known as similarity transformation. The proposed algorithm utilized information-theoretic ideas for image registration. Registration is assumed to correspond to maximizing mutual information. Mutual information compares the statistical dependence between two images. Here experiments are carried out on Brain images. For CT scan and MRI scan, patients needs to lie still. There may be some discomfort from having to remain still for several minutes for some patients having chronic pain or specially for children. So resultant CT scan or MRI scan may be rotated, scaled or translated. So it must be registered correctly as reference image for diagnosis purpose. Simulations are shown which shows the performance of the method presented.
机译:图像配准是将通过在不同时间或从不同角度对同一场景或对象采样而获得的不同数据集转换为一个坐标系的过程。本文提出了一种从两个图像中恢复平移参数的算法,该图像通过旋转,缩放,变换和旋转比例平移(RST)而不同,也称为相似变换。该算法利用信息理论的思想进行图像配准。假定注册对应于最大化互信息。相互信息比较两个图像之间的统计依赖性。在这里,实验是在大脑图像上进行的。对于CT扫描和MRI扫描,患者需要保持静止。对于某些患有慢性疼痛的患者或特别是对于儿童,必须保持静止几分钟可能会有些不适。因此,可以旋转,缩放或平移所得的CT扫描或MRI扫描。因此,必须正确将其注册为参考图像以进行诊断。仿真显示了所提出的方法的性能。

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