Real space iterative reconstruction for vector tomography (RESIRE-V)
- University of California, Los Angeles, CA (United States)
- University of California, Los Angeles, CA (United States); Soochow University, Suzhou (China)
Tomography has had an important impact on the physical, biological, and medical sciences. To date, most tomographic applications have been focused on 3D scalar reconstructions. However, in some crucial applications, vector tomography is required to reconstruct 3D vector fields such as the electric and magnetic fields. Over the years, several vector tomography methods have been developed. Here, we present the mathematical foundation and algorithmic implementation of REal Space Iterative REconstruction for Vector tomography, termed RESIRE-V. RESIRE-V uses multiple tilt series of projections and iterates between the projections and a 3D reconstruction. Each iteration consists of a forward step using the Radon transform and a backward step using its transpose, then updates the object via gradient descent. Incorporating with a 3D support constraint, the algorithm iteratively minimizes an error metric, defined as the difference between the measured and calculated projections. The algorithm can also be used to refine the tilt angles and further improve the 3D reconstruction. To validate RESIRE-V, we first apply it to a simulated data set of the 3D magnetization vector field, consisting of two orthogonal tilt series, each with a missing wedge. Our quantitative analysis shows that the three components of the reconstructed magnetization vector field agree well with the ground-truth counterparts. We then use RESIRE-V to reconstruct the 3D magnetization vector field of a ferromagnetic meta-lattice consisting of three tilt series. Our 3D vector reconstruction reveals the existence of topological magnetic defects with positive and negative charges. We expect that RESIRE-V can be incorporated into different imaging modalities as a general vector tomography method. To make the algorithm accessible to a broad user community, we have made our RESIRE-V MATLAB source codes and the data freely available at https://github.com/minhpham0309/RESIRE-V.
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). Advanced Light Source (ALS)
- Sponsoring Organization:
- National Science Foundation (NSF); U.S. Air Force Office Multidisciplinary University Research Initiative (MURI); USDOE Office of Science (SC), Basic Energy Sciences (BES)
- Grant/Contract Number:
- AC02-05CH11231
- OSTI ID:
- 2471048
- Journal Information:
- Scientific Reports, Journal Name: Scientific Reports Journal Issue: 1 Vol. 14; ISSN 2045-2322
- Publisher:
- Nature Publishing GroupCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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