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Scattering and Imaging with Diffusing Temporal Field Correlations
Abstract
We consider the transport of the electric field temporal autocorrelation in heterogeneous, fluctuating turbid media. Experiments are performed in strongly scattering media with spatially separated static and dynamic components, and low resolution ``dynamical'' images of such media are obtained using autocorrelation measurements of the emerging speckle fields taken along the sample surface. Our analysis, based on a diffusion approximation to the field correlation transport equation, reveals that the field correlation scatters from macroscopic dynamical heterogeneities within turbid media.
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Cited by
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Kim, M. N., Durduran, T., Frangos, S., Edlow, B. L., Buckley, E. M., Moss, H. E., Zhou, C., Yu, G., Choe, R., Maloney-Wilensky, E., et al. (2010) · Neurocritical Care · doi:10.1007/s12028-009-9305-x · Cited by 306
Self-citationExploring early human brain development with structural and physiological neuroimaging
Vasung, L., Abaci Turk, E., Ferradal, S. L., Sutin, J., Stout, J. N., Ahtam, B., Lin, P.-Y., & Grant, P. E. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.07.041 · Cited by 177
Gurley, K., Shang, Y., & Yu, G. (2012) · Journal of Biomedical Optics · doi:10.1117/1.jbo.17.7.075010 · Cited by 81
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Metadata
- Authors
- Boas, D. A., Campbell, L. E., & Yodh, A. G.
- Venue
- Physical Review Letters
- Publisher
- American Physical Society (APS)
- Published
- 1995-08-28
- Volume
- 75
- Issue
- 9
- Pages
- 1855-1858
- ISSN
- 0031-9007 (ISSN-L)
- 1079-7114
- OpenAlex
- W2073494245
- Cited by
- 519
- References
- 0
- FWCI
- 5.06
- Type
- journal article
- Language
- en
- Open access
- closed
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- Boas, D. A., Campbell, L. E., & Yodh, A. G. (1995). Scattering and Imaging with Diffusing Temporal Field Correlations. Physical Review Letters. https://doi.org/10.1103/physrevlett.75.1855
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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.