Work

Uncertainty quantification of Abel inversion in multi-energy x-ray radiography with spatially varying noise

Year: 2025

Type: article

Abstract: Abel inversion is a classical technique for reconstructing the volumetric density of axisymmetric objects from line-integral projections in x-ray radiography. However, traditional methods often rely on simplifying assumptions such as monochromatic x-ray sources and homoscedastic Gaussian noise, which do not hold in practical experiments such as micron-ejecta studies. This paper presents a hierarchical Bayesian framework with Markov Chain Monte Carlo sampling for uncertainty quantification in Abel inversion under more realistic conditions, including polychromatic x-ray spectra and spatially varying noise. We introduce a “step wedge method” to calibrate the energy spectrum and noise characteristics and propose a modified prior structure to improve reconstruction accuracy near the symmetry axis. The method is validated on both synthetic and real experimental data from a 4 MeV pulsed x-ray radiography system. Results demonstrate accurate density reconstruction with explicit uncertainty bounds, highlighting the method’s robustness and applicability in dynamic imaging diagnostics.

Source: AIP Advances

DOI: 10.1063/5.0285733

Authors: Zhipeng Tang, Yonghong Guan, Xuejun Wang, Yuefeng Jing

Institutions: China Academy of Engineering Physics, Institute of Fluid Physics

Language: English

Topic: Numerical methods in inverse problems

Subfield: Mathematical Physics

Field: Mathematics

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,350

Funders: China Academy of Engineering Physics, National Key Laboratory of Shockwave and Detonation Physics