论文标题
一种用于表征3D形状的新的基于测量的特征：适用于软组织器官的时间变形
A new geodesic-based feature for characterization of 3D shapes: application to soft tissue organ temporal deformations
论文作者
论文摘要
在本文中，我们提出了一种表征从点云的3D形状的方法，并在器官时间变形的研究中显示了直接应用。举例来说，我们表征了膀胱在强制呼吸运动中的行为，其3D表面点减少了：首先，使用大型动态MRI序列在第一个时间范围内追踪了第一次表面的四边形网格顶点的一组等距点，并使用较大的动态MRI序列使用较大的动态MRI序列使用较大的DiffeOmoration DiffeOmoration DiffeoMoration DiffeOmoration DiffeoMorphic Mapping Mapping（lddmmmpapping）。其次，提出了一种新颖的几何特征，它是通过使用Eulerian偏微分方程（PDES）方法来表征时间器官变形的缩放和旋转的。我们证明了我们特征在合成3D形状和现实动态MRI数据上的鲁棒性，这些数据描绘了强制呼吸运动过程中膀胱变形。获得了有希望的结果，表明所提出的功能可能对几种计算机视觉应用有用，例如医学成像，空气动力学和机器人技术。
In this paper, we propose a method for characterizing 3D shapes from point clouds and we show a direct application on a study of organ temporal deformations. As an example, we characterize the behavior of a bladder during a forced respiratory motion with a reduced number of 3D surface points: first, a set of equidistant points representing the vertices of quadrilateral mesh for the surface in the first time frame are tracked throughout a long dynamic MRI sequence using a Large Deformation Diffeomorphic Metric Mapping (LDDMM) framework. Second, a novel geometric feature which is invariant to scaling and rotation is proposed for characterizing the temporal organ deformations by employing an Eulerian Partial Differential Equations (PDEs) methodology. We demonstrate the robustness of our feature on both synthetic 3D shapes and realistic dynamic MRI data portraying the bladder deformation during forced respiratory motions. Promising results are obtained, showing that the proposed feature may be useful for several computer vision applications such as medical imaging, aerodynamics and robotics.
