The DOI matches its Crossref record.
Computed Tomography: Principles, Design, Artifacts, and Recent Advances
Abstract
X-ray computed tomography (CT) has experienced an explosion of technological development for a quarter century. Six years after the second edition of Computed Tomography, this third edition captures the most recent advances in technology and clinical applications. New to this edition are descriptions of iterative reconstruction, statistical reconstruction, methodologies used to model the CT systems, and the searching methodologies for optimal solutions. A new section on 3D printing introduces approaches by early adopters in the area. Also added is a description and discussion of the size-specific dose estimate, an index that attempts to more accurately reflect the dose absorption of specific-sized patients. The coverage of dual-energy CT has been significantly expanded to include its background, theoretical development, and clinical applications
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
Cited by
Artifacts in CT: Recognition and Avoidance
Barrett, J. F., & Keat, N. (2004) · RadioGraphics · doi:10.1148/rg.246045065 · Cited by 1,688
Metscher, B. D. (2009) · BMC Physiology · doi:10.1186/1472-6793-9-11 · Cited by 1,086
AI in Medical Imaging Informatics: Current Challenges and Future Directions
Panayides, A. S., Amini, A., Filipovic, N. D., Sharma, A., Tsaftaris, S. A., Young, A., Foran, D., Do, N., Golemati, S., Kurc, T., et al. (2020) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2020.2991043 · Cited by 713
Landis, E. N., & Keane, D. T. (2010) · Materials Characterization · doi:10.1016/j.matchar.2010.09.012 · Cited by 608
Sombke, A., Lipke, E., Michalik, P., Uhl, G., & Harzsch, S. (2015) · Journal of Comparative Neurology · doi:10.1002/cne.23741 · Cited by 144
Metadata
- Authors
- Hsieh, J.
- Publisher
- SPIE PRESS
- Published
- 2015
- OpenAlex
- W1556473642
- Cited by
- 1,400
- References
- 0
- FWCI
- 82.14
- 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.
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: Computed Tomography: Principles, Design, Artifacts, and Recent Advances. https://app.cochat.ai/papers/10.1117/3.2197756
- The paper
- Hsieh, J. (2015). Computed Tomography: Principles, Design, Artifacts, and Recent Advances. https://doi.org/10.1117/3.2197756
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.