Nonrigid image registration with two-sided space-fractional partial differential equations
Nonrigid image registration with two-sided space-fractional partial differential equations
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DOI：
10.1109/icip.2013.6738154
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Clarissa C. Garvey;N. Cahill;A. Melbourne;C. Tanner;S. Ourselin;D. Hawkes
中科院分区：
文献类型：
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作者：
Clarissa C. Garvey;N. Cahill;A. Melbourne;C. Tanner;S. Ourselin;D. Hawkes
分数阶偏微分方程组可以用来模拟超扩散过程。最近对分数偏微分方程组的研究探索了它们对非刚性图像配准的影响，非刚性图像配准通常使用整数阶的微分算子。在本文中，我们提出了一种非刚性配准算法，该算法涉及在每个时间步长上直接快速地求解受物理真实图像边界条件约束的离散化的分数偏微分方程组。通过对模拟生物力学变形的乳腺MR图像的配准实验验证了该算法的有效性，结果表明，超扩散模型比基于扩散的标准配准方法具有更低的平均变形误差。
Fractional partial differential equations can be used to model super-diffusive processes. Recent research into fractional PDEs has explored their impact on nonrigid image registration, which typically uses differential operators of integer order. In this paper, we propose a nonrigid registration algorithm that involves directly and rapidly solving a discretized fractional PDE at each time step that is subject to physically realistic image boundary conditions. The proposed algorithm is validated through registration experiments on breast MR imagery with simulated biomechanical deformations, indicating that the super-diffusive model yields lower average deformation errors than standard diffusion-based registration.