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The DOI matches its Crossref record; 311 of the 311 references it cites were found in a registry or an index.

Diffuse optics for tissue monitoring and tomography

Open access
Durduran, T, Choe, R, Baker, W B, Yodh, A G·2010·Reports on Progress in Physics

Abstract

This review describes the diffusion model for light transport in tissues and the medical applications of diffuse light. Diffuse optics is particularly useful for measurement of tissue hemodynamics, wherein quantitative assessment of oxy- and deoxy-hemoglobin concentrations and blood flow are desired. The theoretical basis for near-infrared or diffuse optical spectroscopy (NIRS or DOS, respectively) is developed, and the basic elements of diffuse optical tomography (DOT) are outlined. We also discuss diffuse correlation spectroscopy (DCS), a technique whereby temporal correlation functions of diffusing light are transported through tissue and are used to measure blood flow. Essential instrumentation is described, and representative brain and breast functional imaging and monitoring results illustrate the workings of these new tissue diagnostics.

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Crossref · 10.1088/0034-4885/73/7/076701

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Metadata

Authors
Durduran, T., Choe, R., Baker, W. B., & Yodh, A. G.
Venue
Reports on Progress in Physics
Published
2010-06-02
Volume
73
Issue
7
Pages
076701
ISSN
  • 0034-4885 (ISSN-L)
  • 1361-6633
OpenAlex
W2061135416
Cited by
1,161
References
311
FWCI
24.59
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Diffuse optics for tissue monitoring and tomography. https://app.cochat.ai/papers/10.1088/0034-4885/73/7/076701
The paper
Durduran, T., Choe, R., Baker, W. B., & Yodh, A. G. (2010). Diffuse optics for tissue monitoring and tomography. Reports on Progress in Physics. https://doi.org/10.1088/0034-4885/73/7/076701

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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.