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Metal-related artifacts in instrumented spine. Techniques for reducing artifacts in CT and MRI: state of the art
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Citations
Cited by
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Wang, J., Xu, J., Hopkins, C., Chow, D. H., & Qin, L. (2020) · Advanced Science · doi:10.1002/advs.201902443 · Cited by 574
Review of medical image quality assessment
Chow, L. S., & Paramesran, R. (2016) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2016.02.006 · Cited by 265
Metadata
- Authors
- Stradiotti, P., Curti, A., Castellazzi, G., & Zerbi, A.
- Venue
- European Spine Journal
- Published
- 2009-05-13
- Volume
- 18
- Issue
- S1
- Pages
- 102-108
- ISSN
- 0940-6719 (ISSN-L)
- 1432-0932
- OpenAlex
- W2081830027
- Cited by
- 241
- References
- 0
- FWCI
- 5.82
- Type
- journal article
- Language
- en
- Open access
- bronze
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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.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: Metal-related artifacts in instrumented spine. Techniques for reducing artifacts in CT and MRI: state of the art. https://app.cochat.ai/papers/10.1007/s00586-009-0998-5
- The paper
- Stradiotti, P., Curti, A., Castellazzi, G., & Zerbi, A. (2009). Metal-related artifacts in instrumented spine. Techniques for reducing artifacts in CT and MRI: state of the art. European Spine Journal. https://doi.org/10.1007/s00586-009-0998-5
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.
