AI-Assisted Coherent Raman Scattering Microscopy for Clinical Translation
Coherent Raman scattering (CRS) microscopy has emerged as a powerful bioimaging tool, combining bond-specific contrast with high sensitivity, to enable rapid histopathology and metabolic analysis. Yet, clinical translation demands further breakthroughs in acquisition speed, spatial/spectral resolution, imaging depth, and data interpretation. While hardware advances address some constraints, artificial intelligence (AI) now propels the field forward by decoding biological complexity beyond traditional limits. This review summarizes representative clinical applications of CRS microscopy, highlighting how AI-driven innovations are bridging technological gaps and accelerating deployment in medical diagnostics and research.
Authors
- Kuan Luo (ORCID: https://orcid.org/0009-0001-2661-1577)
- Yue Yu (ORCID: https://orcid.org/0000-0003-0633-9577)
- Yuheng Guo
- Minbiao Ji
Institutions
- Fudan University (CN)
Publication Details
- Journal
- Chemical & Biomedical Imaging
- Published
- 2026-01-07
- DOI
- https://doi.org/10.1021/cbmi.5c00199
- Primary Topic
- Spectroscopy Techniques in Biomedical and Chemical Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00