An O(N log N) algorithm for shape modeling.

We present a shape-recovery technique in two dimensions and three dimensions with specific applications in modeling anatomical shapes from medical images. This algorithm models extremely corrugated structures like the brain, is topologically adaptable, and runs in O(N log N) time, where N is the total number of points in the domain. Our technique is based on a level set shape-recovery scheme recently introduced by the authors and the fast marching method for computing solutions to static Hamilton-Jacobi equations. IMAGES:

我们提出了一种适用于二维与三维场景的形状恢复技术，其特定应用场景为从医学影像中建模解剖结构形态。该算法可对大脑这类高度褶皱的结构进行建模，具备拓扑适应性，且运行时间复杂度为O(N log N)，其中N为计算域内的总点数。我们的技术基于作者近期提出的水平集（level set）形状恢复框架，以及用于求解静态哈密顿-雅可比（Hamilton-Jacobi）方程的快速行进法（fast marching method）。影像：