Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 381

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

Multi–Detector Row CT Systems and Image-Reconstruction Techniques

Flohr, Thomas G., Schaller, Stefan, Stierstorfer, Karl, Bruder, Herbert, Ohnesorge, Bernd M., Schoepf, U. Joseph·2005·Radiology

Abstract

The introduction in 1998 of multi-detector row computed tomography (CT) by the major CT vendors was a milestone with regard to increased scan speed, improved z-axis spatial resolution, and better utilization of the available x-ray power. In this review, the general technical principles of multi-detector row CT are reviewed as they apply to the established four- and eight-section systems, the most recent 16-section scanners, and future generations of multi-detector row CT systems. Clinical examples are used to demonstrate both the potential and the limitations of the different scanner types. When necessary, standard single-section CT is referred to as a common basis and starting point for further developments. Another focus is the increasingly important topic of patient radiation exposure, successful dose management, and strategies for dose reduction. Finally, the evolutionary steps from traditional single-section spiral image-reconstruction algorithms to the most recent approaches toward multisection spiral reconstruction are traced.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1148/radiol.2353040037

Cites

1 of 1 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 1 references

Cited by

See all 381

Metadata

Authors
Flohr, T. G., Schaller, S., Stierstorfer, K., Bruder, H., Ohnesorge, B. M., & Schoepf, U. J.
Venue
Radiology
Published
2005-06
Volume
235
Issue
3
Pages
756-773
ISSN
  • 0033-8419 (ISSN-L)
  • 1527-1315
OpenAlex
W2159519445
Cited by
381
References
1
FWCI
26.66
Type
journal article
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: Multi–Detector Row CT Systems and Image-Reconstruction Techniques. https://app.cochat.ai/papers/10.1148/radiol.2353040037
The paper
Flohr, T. G., Schaller, S., Stierstorfer, K., Bruder, H., Ohnesorge, B. M., & Schoepf, U. J. (2005). Multi–Detector Row CT Systems and Image-Reconstruction Techniques. Radiology. https://doi.org/10.1148/radiol.2353040037

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.