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Log-Demons with driving force for large deformation image registration

机译:具有驱动力的Log-Demons用于大变形图像配准

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Capturing large diffeomorphic deformations is difficult for many non-rigid registration methods. In this paper, we propose Log-Demons with driving force for large deformation image registration. The driving force obtained by boundary points correspondence exerts influence on continuous optimization of Log-Demons to improve the motion direction of points. We utilize MROGH descriptor matching to obtain points correspondence as driving force, then the driving force is added to the optimization of Log-Demons. We integrate the driving force in an exponentially decreasing form with velocity field of Log-Demons to drive the points moving globally and to speed up the convergence. Experiments performed on synthetic images, real scene images and brain images demonstrate that the proposed method can not only capture large deformations but also preserve details and register images at a higher accuracy.
机译:对于许多非刚性登记方法难以捕获大的漫射形式变形。在本文中,我们提出了具有大变形图像配准的驱动力的降低恶魔。边界点对应获得的驱动力对日志恶魔的连续优化产生影响以改善点的运动方向。我们利用MROGH描述符匹配以获得点对应关系作为驱动力,然后将驱动力添加到日志恶魔的优化中。我们以指数递减的形式集成了驱动力,具有日志恶魔的速度场,以驱动全球的点,并加快收敛。对合成图像,真实场景图像和大脑图像进行的实验表明,所提出的方法不仅可以捕获大变形,还可以以更高的精度捕获细节并寄存图像。

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