The Sinogram Polygonizer for Reconstructing 3D Shapes
The Sinogram Polygonizer for Reconstructing 3D Shapes
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用于重建 3D 形状的 Sinogram Polygonizer
DOI：
10.1109/tvcg.2013.87
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Hiromasa Suzuki
中科院分区：
文献类型：
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作者：
Daiki Yamanaka;Yutaka Ohtake;Hiromasa Suzuki
本文提出了一种新的方法，正弦图重建器，用于直接从正弦图重建3D形状（即，来自X射线计算机断层摄影（CT）扫描仪的主要输出，包括从不同视角显示的对象的投影图像序列）。为了获得近似扫描对象的表面的多边形网格，基于网格的等值面拟合器（isosurfacetizer）（诸如Marching Cubes）已经常规地应用于从正弦图重建的CT体积。相比之下，所提出的方法将CT值视为连续函数，并直接提取三角形网格的四面体网格变形的基础上。这种变形涉及二次误差度量最小化和最佳Delaunay三角剖分，以生成准确，高质量的网格。由于CT值的分析梯度估计，即使生成的网格非常粗糙，也可以很好地近似尖锐的特征。此外，该方法消除了三角形网格上的锯齿伪影。
This paper proposes a novel approach, the sinogram polygonizer, for directly reconstructing 3D shapes from sinograms (i.e., the primary output from X-ray computed tomography (CT) scanners consisting of projection image sequences of an object shown from different viewing angles). To obtain a polygon mesh approximating the surface of a scanned object, a grid-based isosurface polygonizer, such as Marching Cubes, has been conventionally applied to the CT volume reconstructed from a sinogram. In contrast, the proposed method treats CT values as a continuous function and directly extracts a triangle mesh based on tetrahedral mesh deformation. This deformation involves quadratic error metric minimization and optimal Delaunay triangulation for the generation of accurate, high-quality meshes. Thanks to the analytical gradient estimation of CT values, sharp features are well approximated, even though the generated mesh is very coarse. Moreover, this approach eliminates aliasing artifacts on triangle meshes.