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A Novel Deformable Image Registration Algorithm Based on Improved Active Demons

机译:一种基于改进活性恶魔的新型可变形图像配准算法

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The optical flow field-based active demons algorithm is a major technique for nonrigid image registration. Current active demons algorithms for large deformation problems are suffered with low registration precision due to using gradient information of the reference image and moving image only. To avoid the disadvantage of the active demons algorithms, this paper first presents the length and area of connected region as driving forces into the active demons diffusion equation and then proposes a new deformable image registration algorithm by combining the gradient information-based driving forces and connected region-based driving forces. Furthermore, a multi-resolution technique is introduced for robust performance against noise. Experimental results show that the proposed deformable image registration algorithm has better performance than several conventional active demons algorithms.
机译:基于光学流场的有源恶魔算法是非重力图像配准的主要技术。由于仅使用参考图像和运动图像的梯度信息,因此由于使用参考图像和运动图像的梯度信息而遭受了大变形问题的电流活跃的探测器。为了避免有源恶魔算法的缺点,本文首先将连接区域的长度和面积呈现为驱动力进入有源恶魔扩散方程,然后通过组合基于梯度信息的驱动力和连接来提出新的可变形图像配准算法基于地区的驱动力。此外,引入了一种多分析技术,用于抗噪声的鲁棒性能。实验结果表明,所提出的可变形图像配准算法具有比几个传统的活性Demons算法更好的性能。

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