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2000
Volume 20, Issue 1
  • ISSN: 1573-4056
  • E-ISSN: 1875-6603
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Abstract

Background

Cancer is a major disease that threatens human life and health. Raman spectroscopy can provide an effective detection method.

Objective

The study aimed to introduce the application of Raman spectroscopy to tumor detection. We have introduced the current mainstream Raman spectroscopy technology and related application research.

Methods

This article has first introduced the grim situation of malignant tumors in the world. The advantages of tumor diagnosis based on Raman spectroscopy have also been analyzed. Secondly, various Raman spectroscopy techniques applied in the medical field are introduced. Several studies on the application of Raman spectroscopy to tumors in different parts of the human body are discussed. Then the advantages of combining deep learning with Raman spectroscopy in the diagnosis of tumors are discussed. Finally, the related problems of tumor diagnosis methods based on Raman spectroscopy are pointed out. This may provide useful clues for future work.

Conclusion

Raman spectroscopy can be an effective method for diagnosing tumors. Moreover, Raman spectroscopy diagnosis combined with deep learning can provide more convenient and accurate detection results.

© 2024 The Author(s). Published by Bentham Science Publisher.
This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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2025-08-18

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Research Progress in Tumor Diagnosis Based on Raman Spectroscopy
Curr. Med. Imaging 20, e110823219690 (2024); https://doi.org/10.2174/1573405620666230811142737
/content/journals/cmir/10.2174/1573405620666230811142737
/content/journals/cmir/10.2174/1573405620666230811142737
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  • Article Type:     Review Article
Keyword(s): Deep learning; Medical diagnosis; Peak position; Raman spectroscopy; Tumor; Tumor diagnosis

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