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Cited by 1,080

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Strategies for CT Radiation Dose Optimization

Kalra, Mannudeep K., Maher, Michael M., Toth, Thomas L., Hamberg, Leena M., Blake, Michael A., Shepard, Jo-Anne, Saini, Sanjay·2004·Radiology

Abstract

Recent technologic advances have markedly enhanced the clinical applications of computed tomography (CT). While the benefits of CT exceed the harmful effects of radiation exposure in patients, increasing radiation doses to the population have raised a compelling case for reduction of radiation exposure from CT. Strategies for radiation dose reduction are difficult to devise, however, because of a lack of guidelines regarding CT examination and scanning techniques. Various methods and strategies based on individual patient attributes and CT technology have been explored for dose optimization. It is the purpose of this review article to outline basic principles of CT radiation exposure and emphasize the need for CT radiation dose optimization based on modification of scanning parameters and application of recent technologic innovations.

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Metadata

Authors
Kalra, M. K., Maher, M. M., Toth, T. L., Hamberg, L. M., Blake, M. A., Shepard, J.-A., & Saini, S.
Venue
Radiology
Published
2004-03
Volume
230
Issue
3
Pages
619-628
ISSN
  • 0033-8419 (ISSN-L)
  • 1527-1315
OpenAlex
W2001435563
Cited by
1,080
References
1
FWCI
32.61
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Strategies for CT Radiation Dose Optimization. https://app.cochat.ai/papers/10.1148/radiol.2303021726
The paper
Kalra, M. K., Maher, M. M., Toth, T. L., Hamberg, L. M., Blake, M. A., Shepard, J.-A., & Saini, S. (2004). Strategies for CT Radiation Dose Optimization. Radiology. https://doi.org/10.1148/radiol.2303021726

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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.