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Cited by 281

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

The sensitivity of magnetic resonance image signals of a rat brain to changes in the cerebral venous blood oxygenation

Ogawa, Seiji, Lee, T. M., Barrere, Bertrand·1993·Magnetic Resonance in Medicine

Abstract

The sensitivity of magnetic resonance image signals of the brain to the change in the cerebral blood oxygenation was measured in gradient echo images of rat brains at a field strength of 7 T. The sensitivity depended on the blood vessel volume relative to the tissue volume within the image voxel, and signal intensities in the cortical area were well correlated with the change in the venous blood de‐oxygenation level at the sagittal sinus. Tissue signals in the image (15 ms echo time) showed a sensitivity of 10‐20% change for the full range of deoxygenation level from 0‐100%. From these observations and image simulations, the extent of the signal response to some neuro‐stimulation which induces an increase in regional cerebral blood flow has been estimated for 4 T field strength.

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Crossref · 10.1002/mrm.1910290208

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Metadata

Authors
Ogawa, S., Lee, T. M., & Barrere, B.
Venue
Magnetic Resonance in Medicine
Publisher
Wiley
Published
1993-02
Volume
29
Issue
2
Pages
205-210
ISSN
  • 0740-3194 (ISSN-L)
  • 1522-2594
OpenAlex
W2036158578
Cited by
281
References
7
FWCI
10.59
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The sensitivity of magnetic resonance image signals of a rat brain to changes in the cerebral venous blood oxygenation. https://app.cochat.ai/papers/10.1002/mrm.1910290208
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Ogawa, S., Lee, T. M., & Barrere, B. (1993). The sensitivity of magnetic resonance image signals of a rat brain to changes in the cerebral venous blood oxygenation. Magnetic Resonance in Medicine. https://doi.org/10.1002/mrm.1910290208

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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.