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Cited by 237

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Coherent Raman Scattering Microscopy in Biology and Medicine

Open access
Zhang, Chi, Zhang, Delong, Cheng, Ji-Xin·2015·Annual Review of Biomedical Engineering

Abstract

Advancements in coherent Raman scattering (CRS) microscopy have enabled label-free visualization and analysis of functional, endogenous biomolecules in living systems. When compared with spontaneous Raman microscopy, a key advantage of CRS microscopy is the dramatic improvement in imaging speed, which gives rise to real-time vibrational imaging of live biological samples. Using molecular vibrational signatures, recently developed hyperspectral CRS microscopy has improved the readout of chemical information available from CRS images. In this article, we review recent achievements in CRS microscopy, focusing on the theory of the CRS signal-to-noise ratio, imaging speed, technical developments, and applications of CRS imaging in bioscience and clinical settings. In addition, we present possible future directions that the use of this technology may take.

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Crossref · 10.1146/annurev-bioeng-071114-040554

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Metadata

Authors
Zhang, C., Zhang, D., & Cheng, J.-X.
Venue
Annual Review of Biomedical Engineering
Published
2015-12-07
Volume
17
Issue
1
Pages
415-445
ISSN
  • 1523-9829 (ISSN-L)
  • 1545-4274
OpenAlex
W1848973643
Cited by
237
References
3
FWCI
1.12
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Coherent Raman Scattering Microscopy in Biology and Medicine. https://app.cochat.ai/papers/10.1146/annurev-bioeng-071114-040554
The paper
Zhang, C., Zhang, D., & Cheng, J.-X. (2015). Coherent Raman Scattering Microscopy in Biology and Medicine. Annual Review of Biomedical Engineering. https://doi.org/10.1146/annurev-bioeng-071114-040554

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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.