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Updated: Jun 4, 2026
09:46
Direct Comparison of Hyperspectral Stimulated Raman Scattering and Coherent Anti-Stokes Raman Scattering Microscopy for Chemical Imaging
Published on: April 28, 2022
Hyperspectral coherent anti-Stokes Raman scattering microscopy imaging through turbid medium
Rajan Arora1, Georgi I Petrov, Vladislav V Yakovlev
1University of Wisconsin - Milwaukee, Department of Physics, 1900 East Kenwood Boulevard, Milwaukee, Wisconsin 53211, USA.
Journal of Biomedical Optics
|March 3, 2011
Summary
This study demonstrates advanced coherent Raman imaging for noninvasive chemical analysis. Hierarchical cluster analysis successfully identified distinct chemical species through scattering media, enabling detailed subsurface imaging.
Area of Science:
- Optics and Photonics
- Spectroscopy
- Biomedical Imaging
Background:
- Coherent Raman microspectroscopy imaging offers noninvasive, chemically specific optical analysis.
- Analyzing chemical composition and distribution in biological tissues is crucial for diagnostics.
Purpose of the Study:
- To apply hierarchical cluster analysis to hyperspectral coherent anti-Stokes Raman imaging.
- To demonstrate the capability of imaging and identifying chemical species through scattering media.
Main Methods:
- Hyperspectral coherent anti-Stokes Raman imaging was performed.
- Hierarchical cluster analysis was applied using commercial software (Cytospec, Inc.).
- A phase retrieval algorithm converted coherent anti-Stokes Raman spectra to Raman spectra.
Main Results:
- Distinct chemical species were successfully imaged and identified through a thick scattering medium.
- Hidden microscopic objects were chemically identified using retrieved Raman spectra.
- Successful demonstrations included remote sensing of biological threats and imaging through skin tissue.
Conclusions:
- Hierarchical cluster analysis combined with coherent Raman imaging enables effective chemical identification through scattering media.
- This technique shows significant potential for noninvasive subsurface imaging and remote sensing applications.
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