SurfaceNets for Multi-Label Segmentations with Preservation of Sharp Boundaries.

The Journal of computer graphics techniques Pub Date : 2022-01-01 Epub Date: 2022-02-28
Sarah F Frisken
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Abstract

We extend 3D SurfaceNets to generate surfaces of segmented 3D medical images composed of multiple materials represented as indexed labels. Our extension generates smooth, high-quality triangle meshes suitable for rendering and tetrahedralization, preserves topology and sharp boundaries between materials, guarantees a user-specified accuracy, and is fast enough that users can interactively explore the trade-off between accuracy and surface smoothness. We provide open-source code in the form of an extendable C++ library with a simple API, and a Qt and OpenGL-based application that allows users to import or randomly generate multi-label volumes to experiment with surface fairing parameters. In this paper, we describe the basic SurfaceNets algorithm, our extension to handle multiple materials, our method for preserving sharp boundaries between materials, and implementation details used to achieve efficient processing.

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保留清晰边界的多标签分割曲面。
我们扩展了3D SurfaceNets,以生成由多种材料组成的以索引标签表示的分割三维医学图像的表面。我们的扩展生成适合渲染和四面体化的光滑,高质量的三角形网格,保留材料之间的拓扑和尖锐边界,保证用户指定的精度,并且足够快,用户可以交互式地探索精度和表面平滑之间的权衡。我们提供了一个可扩展的c++库形式的开源代码和一个简单的API,以及一个基于Qt和opengl的应用程序,允许用户导入或随机生成多标签卷来实验表面整流罩参数。在本文中,我们描述了基本的SurfaceNets算法,我们处理多个材料的扩展,我们在材料之间保持清晰边界的方法,以及用于实现高效处理的实现细节。
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SurfaceNets for Multi-Label Segmentations with Preservation of Sharp Boundaries.
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