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3D Image Reconstruction for Implosion Pellet in ICF Experiment Based on Iterative Algorithms

机译:基于迭代算法的ICF实验中爆丸的3D图像重建

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The projection images of implosion-pellet captured by framing cameras or pinhole cameras are two-dimensional in the inertia confinement fusion experiments. Since the two-dimensional images are lack of the depth information, therefore they are hardly used to diagnose the compression symmetry of the implosion-pellet, the 3D image of the implosion-pellet reconstructed from their two-dimensional projection images can overcome these problems. As the iterative algorithms can reconstruct the original 3D image from just a few projections with good noise suppression, three iterative algorithms which are commonly applied in CT image reconstruction filed are utilized to the reconstruct 3D image of implosion-pellet. The numerical simulations show that the algebraic reconstruction technique algorithm performs best under the condition that the projection images are ?incomplete? and noise free or with not so heavy noise. When there are heavy noise in the projection images the simultaneous iterative reconstruction technique surpasses the other algorithms, which is proved to be more competent for the 3D image reconstruction of implosion-pellet in inertia confinement fusion experiment.
机译:在惯性约束融合实验中,由成帧照相机或针孔照相机捕获的内爆弹丸的投影图像是二维的。由于二维图像缺少深度信息,因此很难用于诊断内爆弹丸的压缩对称性,因此由其二维投影图像重建的内爆弹丸的3D图像可以克服这些问题。由于迭代算法可以从几个投影中重建出原始的3D图像,并且具有良好的噪声抑制效果,因此将CT图像重建领域常用的三种迭代算法用于内爆弹丸的3D图像重建。数值仿真表明,在投影图像“不完整”的情况下,代数重构技术算法的性能最佳。无噪音或噪音不大。当投影图像中存在大量噪声时,同步迭代重建技术优于其他算法,这在惯性约束融合实验中被证明对爆破弹丸的3D图像重建具有更强的能力。

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