Deformable templates using large deformation kinematics
Deformable templates using large deformation kinematics
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DOI：
10.1109/83.536892
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发表时间：
1996-10-01
影响因子：
10.6
通讯作者：
Miller, MI
中科院分区：
文献类型：
--
作者：
Christensen, GE;Rabbitt, RD;Miller, MI
提出了一种通用的自动方法，用于在将二维（2 - D）或三维（3 - D）模板图像映射到与拓扑相似的目标图像对齐时适应局部形状变化。通过对模板的基础材料坐标系应用向量场变换来适应局部形状可变性，同时约束该变换是平滑的（全局正定雅可比行列式）。通过基于流体动力学纳维 - 斯托克斯方程的斯托克斯极限约束变换，在不特别惩罚小子体积的大幅度变形的情况下保证了平滑性。这与二次惩罚方法（例如基于线性弹性或薄板样条的方法）从根本上不同，因为约束运动的应力会随着时间松弛，从而允许大幅度变形。在大幅度变形期间，运动非线性对于保持结构的连续性是固有必要的，并且包含在所有结果中。在初始全局配准之后，通过数值求解与约束优化问题相关的一组非线性偏微分方程来获得最终映射。当在有限晶格上评估的非线性变换变得奇异时，通过传播模板来执行自动重新网格化。将该方法应用于神经解剖结构的个体间配准，说明了其考虑局部解剖可变性的能力。
A general automatic approach is presented for accommodating local shape variation when mapping a two-dimensional (2-D) or three-dimensional (3-D) template image into alignment with a topologically similar target image, Local shape variability is accommodated by applying a vector-field transformation to the underlying material coordinate system of the template while constraining the transformation to be smooth (globally positive definite Jacobian), Smoothness is guaranteed without specifically penalizing large-magnitude deformations of small subvolumes by constraining the transformation on the basis of a Stokesian limit of the fluid-dynamical Navier-Stokes equations, This differs fundamentally from quadratic penalty methods, such as those based on linearized elasticity or thin-plate splines, in that stress restraining the motion relaxes over time allowing large-magnitude deformations, Kinematic nonlinearities are inherently necessary to maintain continuity of structures during large-magnitude deformations, and are included in all results, After initial global registration, final mappings are obtained by numerically solving a set of nonlinear partial differential equations associated with the constrained optimization problem, Automatic regridding is performed by propagating templates as the nonlinear transformations evaluated on a finite lattice become singular, Application of the method to intersubject registration of neuroanatomical structures illustrates the ability to account for local anatomical variability.