The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Fast and flexible X-ray tomography using the ASTRA toolbox
Open accessAbstract
Object reconstruction from a series of projection images, such as in computed tomography (CT), is a popular tool in many different application fields. Existing commercial software typically provides sufficiently accurate and convenient-to-use reconstruction tools to the end-user. However, in applications where a non-standard acquisition protocol is used, or where advanced reconstruction methods are required, the standard software tools often are incapable of computing accurate reconstruction images. This article introduces the ASTRA Toolbox. Aimed at researchers across multiple tomographic application fields, the ASTRA Toolbox provides a highly efficient and highly flexible open source set of tools for tomographic projection and reconstruction. The main features of the ASTRA Toolbox are discussed and several use cases are presented.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
Beck, A., & Teboulle, M. (2009) · SIAM Journal on Imaging Sciences · doi:10.1137/080716542 · Cited by 11,952
Palenstijn, W. J., Batenburg, K. J., & Sijbers, J. (2011) · Journal of Structural Biology · doi:10.1016/j.jsb.2011.07.017 · Cited by 384
Self-citation
Cited by
Learned Primal-Dual Reconstruction
Adler, J., & Oktem, O. (2018) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2018.2799231 · Cited by 758
Metadata
- Authors
- van Aarle, W., Palenstijn, W. J., Cant, J., Janssens, E., Bleichrodt, F., Dabravolski, A., De Beenhouwer, J., Joost Batenburg, K., & Sijbers, J.
- Venue
- Optics Express
- Publisher
- Optica Publishing Group
- Published
- 2016-10-19
- Volume
- 24
- Issue
- 22
- Pages
- 25129
- ISSN
- 1094-4087 (ISSN-L)
- OpenAlex
- W2533020866
- Cited by
- 1,036
- References
- 2
- FWCI
- 60.87
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Fast and flexible X-ray tomography using the ASTRA toolbox. https://app.cochat.ai/papers/10.1364/oe.24.025129
- The paper
- van Aarle, W., Palenstijn, W. J., Cant, J., Janssens, E., Bleichrodt, F., Dabravolski, A., De Beenhouwer, J., Joost Batenburg, K., & Sijbers, J. (2016). Fast and flexible X-ray tomography using the ASTRA toolbox. Optics Express. https://doi.org/10.1364/oe.24.025129
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.