In this paper, we propose a new approach to deformable image registration that captures sliding motions. The large deformation diffeomorphic metric mapping (LDDMM) registration method faces challenges in representing sliding motion since it per construction generates smooth warps. To address this issue, we extend LDDMM by incorporating both zeroth- and first-order momenta with a non-differentiable kernel. This allows to represent both discontinuous deformation at switching boundaries and diffeomorphic deformation in homogeneous regions. We provide a mathematical analysis of the proposed deformation model from the viewpoint of discontinuous systems. To evaluate our approach, we conduct experiments on both artificial images and the publicly available DIR-Lab 4DCT dataset. Results show the effectiveness of our approach in capturing plausible sliding motion.
翻译:在本文中,我们提出一种新的可变化图像登记方法,以捕捉滑动。大型变形二变形基准绘图(LDDMM)登记方法在代表滑动运动方面面临着挑战,因为每次施工都会产生滑动曲折曲。为了解决这一问题,我们扩展LDDMMM方法,将零级和一阶的瞬间和无差别的内核都纳入其中。这既能代表改变边界时的不连续变形,又能代表同一区域的二变形变形。我们从不连续系统的角度对拟议的变形模型进行了数学分析。为了评估我们的方法,我们进行了人工图象实验,以及可公开查阅的DIR-Lab 4DCT数据集。结果显示了我们在捕捉貌似滑动运动方面的有效性。</s>