Frontiers in Physics | |
High-energy X-ray spectrum reconstruction: solving the inverse problem from optimized multi-material transmission measurements | |
Physics | |
A. Walker1  K. Ginsburger1  A. Friou2  | |
[1] CEA, DAM, DIF, Arpajon, France;null; | |
关键词: spectrum estimation; flash X-ray; transmission measurement; genetic algorithm; ill-posed inverse problem; | |
DOI : 10.3389/fphy.2023.1257548 | |
received in 2023-07-12, accepted in 2023-08-28, 发布年份 2023 | |
来源: Frontiers | |
【 摘 要 】
Reconstructing the unknown spectrum of a given X-ray source is a common problem in a wide range of X-ray imaging tasks. For high-energy sources, transmission measurements are mostly used to recover the X-ray spectrum, as a solution to an inverse problem. While this inverse problem is usually under-determined, ill-posedness can be reduced by improving the choice of transmission measurements. A recently proposed approach optimizes custom thicknesses of calibration materials used to generate transmission measurements, employing a genetic algorithm to minimize the condition number of the system matrix before inversion. In this paper, we generalize the proposed approach to multiple calibration materials and show a much larger decrease of the condition number of the system matrix than thickness-only optimization. Additionally, the spectrum reconstruction pipeline is tested in a simulation study with a challenging high-energy Bremsstrahlung X-ray source encountered in Linear Induction Accelerators with strong scatter noise. Using this approach, a realistic noise level is obtained on measurements. A generic anti-scatter grid is designed to reduce noise to an acceptable -yet still high-noise range. A novel noise-robust reconstruction method is then presented, which shows much less sensitive to initialization than common expectation-maximization approaches, enables a precise choice of spectrum resolution and a controlled injection of prior knowledge of the X-ray spectrum.
【 授权许可】
Unknown
Copyright © 2023 Walker, Friou and Ginsburger.
【 预 览 】
Files | Size | Format | View |
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RO202310122499819ZK.pdf | 2533KB | download |