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Cited by 627

The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.

Three dimensional optical angiography

Open access
Wang, Ruikang K., Jacques, Steven L., Ma, Zhenhe, Hurst, Sawan, Hanson, Stephen R., Gruber, Andras·2007·Optics Express

Abstract

With existing optical imaging techniques three-dimensional (3-D) mapping of microvascular perfusion within tissue beds is severely limited by the efficient scattering and absorption of light by tissue. To overcome these limitations we have developed a method of optical angiography (OAG) that can generate 3-D angiograms within millimeter tissue depths by analyzing the endogenous optical scattering signal from an illuminated sample. The technique effectively separates the moving and static scattering elements within tissue to achieve high resolution images of blood flow, mapped into the 3-D optically sectioned tissue beds, at speeds that allow for perfusion assessment in vivo. Its development has its origin in Fourier domain optical coherence tomography. We used OAG to visualize the cerebral microcirculation, of adult living mice through the intact cranium, measurements which would be difficult, if not impossible, with other optical imaging techniques.

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Metadata

Authors
Wang, R. K., Jacques, S. L., Ma, Z., Hurst, S., Hanson, S. R., & Gruber, A.
Venue
Optics Express
Published
2007-04-02
Volume
15
Issue
7
Pages
4083
ISSN
1094-4087 (ISSN-L)
OpenAlex
W1976553652
Cited by
627
References
22
FWCI
15.54
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Three dimensional optical angiography. https://app.cochat.ai/papers/10.1364/oe.15.004083
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Wang, R. K., Jacques, S. L., Ma, Z., Hurst, S., Hanson, S. R., & Gruber, A. (2007). Three dimensional optical angiography. Optics Express. https://doi.org/10.1364/oe.15.004083

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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.