Simultaneous Sensing Error Recovery and Tomographic Inversion Using an Optimization-Based Approach

Journal Article · Thu May 23 04:00:00 EDT 2019 · SIAM Journal on Scientific Computing

DOI:https://doi.org/10.1137/18M121993X· OSTI ID:1545345

Austin, Anthony P.; Di, Zichao ^[1]; Leyffer, Sven; Wild, Stefan M.

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1. Wendy

Tomography can be used to reveal internal properties of a 3D object using any penetrating wave. Advanced tomographic imaging techniques, however, are vulnerable to both systematic and random errors associated with the experimental conditions, which are often beyond the capabilities of the state-of-the-art reconstruction techniques such as regularizations. Because they can lead to reduced spatial resolution and even misinterpretation of the underlying sample structures, these errors present a fundamental obstacle to full realization of the capabilities of next-generation physical imaging. In this work, we develop efficient and explicit recovery schemes of the most common experimental error: movement of the center of rotation during the experiment. We formulate new physical models to capture the experimental setup, and we devise new mathematical optimization formulations for reliable inversion of complex samples. We demonstrate and validate the efficacy of our approach on synthetic data under known perturbations of the center of rotation.

• Research Organization: Argonne National Laboratory (ANL)
• Sponsoring Organization: USDOE Office of Science - Office of Basic Energy Sciences
• DOE Contract Number: AC02-06CH11357
• OSTI ID: 1545345
• Report Number(s): 9136-0918; 147424
• Journal Information: SIAM Journal on Scientific Computing, Journal Name: SIAM Journal on Scientific Computing Journal Issue: 3 Vol. 41; ISSN 1064-8275
• Country of Publication: United States
• Language: English

Related Subjects

Nonlinear optimization
Self-calibration
Sensing error
Tomographic reconstruction