The DOI matches its Crossref record.
Variational Methods in Imaging
Overview
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Citations
Cited by
Bredies, K., Kunisch, K., & Pock, T. (2010) · SIAM Journal on Imaging Sciences · doi:10.1137/090769521 · Cited by 1,535
Model-Based Learning for Accelerated, Limited-View 3-D Photoacoustic Tomography
Hauptmann, A., Lucka, F., Betcke, M., Huynh, N., Adler, J., Cox, B., Beard, P., Ourselin, S., & Arridge, S. (2018) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2018.2820382 · Cited by 339
Introduction to variational image-processing models and applications
Chen, K. (2013) · International Journal of Computer Mathematics · doi:10.1080/00207160.2012.757073 · Cited by 53
Metadata
- Venue
- Applied Mathematical Sciences
- Publisher
- Springer New York
- Published
- 2009
- ISSN
- 0066-5452 (ISSN-L)
- OpenAlex
- W1544177383
- Cited by
- 462
- References
- 0
- FWCI
- 9.43
- Type
- book
- Language
- en
- Open access
- closed
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.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Variational Methods in Imaging. https://app.cochat.ai/papers/10.1007/978-0-387-69277-7
- The paper
- Variational Methods in Imaging. (2009). Applied Mathematical Sciences. https://doi.org/10.1007/978-0-387-69277-7
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.
