Soldea Octavian, Elber Gershon, Rivlin Ehud
The authors are with the Technion, Israel Institute of Technology, Department of Computer Science, Haifa 32000, Israel.
IEEE Trans Pattern Anal Mach Intell. 2006 Feb;28(2):265-78. doi: 10.1109/TPAMI.2006.36.
This paper presents a method to globally segment volumetric images into regions that contain convex or concave (elliptic) iso-surfaces, planar or cylindrical (parabolic) iso-surfaces, and volumetric regions with saddle-like (hyperbolic) iso-surfaces, regardless of the value of the iso-surface level. The proposed scheme relies on a novel approach to globally compute, bound, and analyze the Gaussian and mean curvatures of an entire volumetric data set, using a trivariate B-spline volumetric representation. This scheme derives a new differential scalar field for a given volumetric scalar field, which could easily be adapted to other differential properties. Moreover, this scheme can set the basis for more precise and accurate segmentation of data sets targeting the identification of primitive parts. Since the proposed scheme employs piecewise continuous functions, it is precise and insensitive to aliasing.
本文提出了一种方法，可将体图像全局分割为包含凸或凹（椭圆形）等值面、平面或圆柱（抛物线形）等值面以及具有鞍状（双曲线形）等值面的体区域，而与等值面水平值无关。所提出的方案依赖于一种新颖的方法，即使用三变量B样条体表示来全局计算、界定和分析整个体数据集的高斯曲率和平均曲率。该方案为给定的体标量场导出一个新的微分标量场，该场可轻松适应其他微分特性。此外，该方案可为以识别原始部分为目标的数据集进行更精确准确的分割奠定基础。由于所提出的方案采用分段连续函数，因此精确且对混叠不敏感。
