Multi-domain, Higher Order Level Set Scheme for 3D Image Segmentation on the GPU.

Ojaswa Sharma, Qin Zhang, François Anton, Chandrajit Bajaj
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引用次数: 11

Abstract

Level set method based segmentation provides an efficient tool for topological and geometrical shape handling. Conventional level set surfaces are only C(0) continuous since the level set evolution involves linear interpolation to compute derivatives. Bajaj et al. present a higher order method to evaluate level set surfaces that are C(2) continuous, but are slow due to high computational burden. In this paper, we provide a higher order GPU based solver for fast and efficient segmentation of large volumetric images. We also extend the higher order method to multi-domain segmentation. Our streaming solver is efficient in memory usage.

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基于GPU的三维图像分割多域高阶水平集方案。
基于水平集的分割方法为拓扑和几何形状的处理提供了有效的工具。传统的水平集曲面只有C(0)连续,因为水平集演化涉及到线性插值来计算导数。Bajaj等人提出了一种高阶方法来评估C(2)连续的水平集曲面,但由于计算负担高而速度很慢。在本文中,我们提供了一个基于高阶GPU的求解器,用于快速有效地分割大体积图像。我们还将高阶方法扩展到多域分割中。我们的流求解器在内存使用方面是高效的。
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