Alscher Thomas, Erleben Kenny, Darkner Sune
Department of Computer Science, University of Copenhagen, Copenhagen, Region Hovedstaden, Denmark.
PLoS One. 2023 Aug 18;18(8):e0290243. doi: 10.1371/journal.pone.0290243. eCollection 2023.
Topological changes like sliding motion, sources and sinks are a significant challenge in image registration. This work proposes the use of the alternating direction method of multipliers as a general framework for constraining the registration of separate objects with individual deformation fields from overlapping in image registration. This constraint is enforced by introducing a collision detection algorithm from the field of computer graphics which results in a robust divide and conquer optimization strategy using Free-Form Deformations. A series of experiments demonstrate that the proposed framework performs superior with regards to the combination of intersection prevention and image registration including synthetic examples containing complex displacement patterns. The results show compliance with the non-intersection constraints while simultaneously preventing a decrease in registration accuracy. Furthermore, the application of the proposed algorithm to the DIR-Lab data set demonstrates that the framework generalizes to real data by validating it on a lung registration problem.
诸如滑动运动、源和汇等拓扑变化是图像配准中的一项重大挑战。这项工作提出使用乘子交替方向法作为一个通用框架，用于在图像配准中约束具有单独变形场的分离对象的配准，以防止它们重叠。通过引入计算机图形学领域的碰撞检测算法来实施这种约束，这产生了一种使用自由形式变形的强大分治优化策略。一系列实验表明，所提出的框架在防止相交和图像配准的组合方面表现出色，包括包含复杂位移模式的合成示例。结果表明符合不相交约束，同时防止配准精度下降。此外，将所提出的算法应用于DIR-Lab数据集表明，该框架通过在肺部配准问题上进行验证而能够推广到真实数据。
