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Related Concept Videos

Raman Spectroscopy Instrumentation: Overview01:26

Raman Spectroscopy Instrumentation: Overview

A conventional Raman spectrophotometer includes a laser source, a sample holding system, a wavelength selector, and a detector.
The monochromatic laser source, typically using visible or near-infrared radiation, generates a highly focused beam of light. This light interacts with the molecules of the sample, scattering some of the light. Liquid and gaseous samples are usually tested in ordinary glass capillaries, while solids can be analyzed as powders packed in capillaries or as potassium...
Raman Spectroscopy: Overview01:20

Raman Spectroscopy: Overview

The underlying principle of Raman spectroscopy is based on the interaction between light and matter, specifically molecules' inelastic scattering of photons. When a monochromatic beam of light, typically from a laser source, interacts with a sample, most scattered light has the same frequency as the incident light. This is known as Rayleigh scattering.
However, a small fraction of the scattered light exhibits a frequency shift due to the exchange of energy between the incident photons and the...
Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...

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Related Experiment Video

Updated: Jun 27, 2026

Implementation of a Coherent Anti-Stokes Raman Scattering (CARS) System on a Ti:Sapphire and OPO Laser Based Standard Laser Scanning Microscope
12:54

Implementation of a Coherent Anti-Stokes Raman Scattering (CARS) System on a Ti:Sapphire and OPO Laser Based Standard Laser Scanning Microscope

Published on: July 17, 2016

AI-Assisted Coherent Raman Scattering Microscopy for Clinical Translation.

Yue Yu1, Yuheng Guo1, Kuan Luo1

  • 1State Key Laboratory of Surface Physics and Department of Physics, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Shanghai Key Laboratory of Metasurfaces for Light Manipulation, Endoscopy Center and Endoscopy Research Institute, Zhongshan Hospital, Fudan University, Shanghai 200433, China.

Chemical & Biomedical Imaging
|June 26, 2026
PubMed
Summary
This summary is machine-generated.

Coherent Raman scattering (CRS) microscopy offers advanced bioimaging for rapid analysis. Artificial intelligence (AI) is now enhancing CRS microscopy, overcoming limitations for improved medical diagnostics and research applications.

Keywords:
artificial intelligenceclinical diagnosiscoherent Raman scatteringcoherent anti-Stokes Raman scattering microscopydeep learninglabel-free histopathologystimulated Raman scattering microscopyvirtual staining

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Real-Time, Two-Color Stimulated Raman Scattering Imaging of Mouse Brain for Tissue Diagnosis
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Real-Time, Two-Color Stimulated Raman Scattering Imaging of Mouse Brain for Tissue Diagnosis

Published on: February 1, 2022

Related Experiment Videos

Last Updated: Jun 27, 2026

Implementation of a Coherent Anti-Stokes Raman Scattering (CARS) System on a Ti:Sapphire and OPO Laser Based Standard Laser Scanning Microscope
12:54

Implementation of a Coherent Anti-Stokes Raman Scattering (CARS) System on a Ti:Sapphire and OPO Laser Based Standard Laser Scanning Microscope

Published on: July 17, 2016

Real-Time, Two-Color Stimulated Raman Scattering Imaging of Mouse Brain for Tissue Diagnosis
10:57

Real-Time, Two-Color Stimulated Raman Scattering Imaging of Mouse Brain for Tissue Diagnosis

Published on: February 1, 2022

Area of Science:

  • Biomedical imaging
  • Spectroscopy
  • Microscopy

Background:

  • Coherent Raman scattering (CRS) microscopy is a potent bioimaging technique.
  • It provides bond-specific contrast and high sensitivity for histopathology and metabolic analysis.
  • Clinical translation requires improvements in speed, resolution, depth, and data interpretation.

Purpose of the Study:

  • To review clinical applications of CRS microscopy.
  • To highlight the role of artificial intelligence (AI) in advancing CRS microscopy.
  • To demonstrate how AI bridges technological gaps in medical diagnostics.

Main Methods:

  • Review of representative clinical applications of CRS microscopy.
  • Analysis of AI-driven innovations in CRS microscopy.
  • Discussion of AI's impact on overcoming current limitations.

Main Results:

  • CRS microscopy is effective for rapid histopathology and metabolic analysis.
  • AI significantly enhances CRS microscopy's capabilities.
  • AI addresses limitations in acquisition speed, resolution, imaging depth, and data interpretation.

Conclusions:

  • AI is crucial for the clinical translation of CRS microscopy.
  • AI-driven innovations accelerate the deployment of CRS microscopy in diagnostics and research.
  • AI decodes biological complexity, pushing the boundaries of traditional bioimaging.