Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 264

The DOI matches its Crossref record.

In vivo small-animal imaging using micro-CT and digital subtraction angiography

Open access
Badea, C T, Drangova, M, Holdsworth, D W, Johnson, G A·2008·Physics in Medicine and Biology

Abstract

Small-animal imaging has a critical role in phenotyping, drug discovery and in providing a basic understanding of mechanisms of disease. Translating imaging methods from humans to small animals is not an easy task. The purpose of this work is to review in vivo x-ray based small-animal imaging, with a focus on in vivo micro-computed tomography (micro-CT) and digital subtraction angiography (DSA). We present the principles, technologies, image quality parameters and types of applications. We show that both methods can be used not only to provide morphological, but also functional information, such as cardiac function estimation or perfusion. Compared to other modalities, x-ray based imaging is usually regarded as being able to provide higher throughput at lower cost and adequate resolution. The limitations are usually associated with the relatively poor contrast mechanisms and potential radiation damage due to ionizing radiation, although the use of contrast agents and careful design of studies can address these limitations. We hope that the information will effectively address how x-ray based imaging can be exploited for successful in vivo preclinical imaging.

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 · 10.1088/0031-9155/53/19/r01

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.

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

Cited by

See all 264

Metadata

Authors
Badea, C. T., Drangova, M., Holdsworth, D. W., & Johnson, G. A.
Venue
Physics in Medicine and Biology
Published
2008-08-29
Volume
53
Issue
19
Pages
R319-R350
ISSN
  • 0031-9155 (ISSN-L)
  • 1361-6560
OpenAlex
W2080799622
Cited by
264
References
0
FWCI
11.47
Type
journal article
Language
en
Open access
bronze

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: In vivo small-animal imaging using micro-CT and digital subtraction angiography. https://app.cochat.ai/papers/10.1088/0031-9155/53/19/r01
The paper
Badea, C. T., Drangova, M., Holdsworth, D. W., & Johnson, G. A. (2008). In vivo small-animal imaging using micro-CT and digital subtraction angiography. Physics in Medicine and Biology. https://doi.org/10.1088/0031-9155/53/19/r01

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.