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

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.