Laboratorio de Procesado de Imagen. ETSI de Telecomunicación, Universidad de Valladolid, Valladolid, Spain.
Health Time Corporation, Córdoba, Spain.
Comput Methods Programs Biomed. 2021 Mar;200:105812. doi: 10.1016/j.cmpb.2020.105812. Epub 2020 Oct 24.
This paper proposes a new and highly efficient implementation of 3D+t groupwise registration based on the free-form deformation paradigm.
Deformation is posed as a cascade of 1D convolutions, achieving great reduction in execution time for evaluation of transformations and gradients.
The proposed method has been applied to 4D cardiac MRI and 4D thoracic CT monomodal datasets. Results show an average runtime reduction above 90%, both in CPU and GPU executions, compared with the classical tensor product formulation.
Our implementation, although fully developed for the metric sum of squared differences, can be extended to other metrics and its adaptation to multiresolution strategies is straightforward. Therefore, it can be extremely useful to speed up image registration procedures in different applications where high dimensional data are involved.
本文提出了一种新的、高效的基于自由变形范例的 3D+t 组配注册实现方法。
变形被表示为一系列 1D 卷积，这极大地减少了变换和梯度评估的执行时间。
该方法已应用于 4D 心脏 MRI 和 4D 胸部 CT 单模态数据集。结果表明，与经典张量积公式相比，在 CPU 和 GPU 执行中，平均运行时间减少了 90%以上。
尽管我们的实现方法完全是针对均方和距离测度开发的，但它可以扩展到其他测度，并且可以直接应用于多分辨率策略。因此，它对于加速涉及高维数据的不同应用中的图像配准过程非常有用。
