Research and application of intelligent hyperspectral analysis technology for Chinese materia medica.
10.19540/j.cnki.cjcmm.20230512.104
- Author:
He WANG
1
;
Shi-Yu LIU
1
;
Hui WANG
2
;
Wei LI
1
;
Meng LYU
1
Author Information
1. Beijing Institute of Technology Beijing 100081,China.
2. National Resource Center for Chinese Materia Medica,Chinese Academy of Chinese Medical Sciences Beijing 100700,China.
- Publication Type:Review
- Keywords:
Chinese materia medica;
hyperspectral imaging technology;
intelligent analysis
- MeSH:
Humans;
Artificial Intelligence;
Drugs, Chinese Herbal;
Hyperspectral Imaging;
Materia Medica;
Medicine, Chinese Traditional;
Technology
- From:
China Journal of Chinese Materia Medica
2023;48(16):4320-4327
- CountryChina
- Language:Chinese
-
Abstract:
With the development of imaging technology and artificial intelligence, hyperspectral imaging technology provides a fast, non-destructive, intelligent, and precise new method for the analysis of Chinese materia medica(CMM). This paper summarized the methods and applications of hyperspectral imaging technology combined with intelligent analysis technology in the field of CMM in recent years, focusing on the acquisition and preprocessing of hyperspectral data, intelligent analysis methods of hyperspectral data, and practical cases of these technologies in the field of CMM. Hyperspectral data of CMM can provide spectral information with nanometer-level resolution and rich spatial texture information simultaneously. This paper summarized the acquisition process, including black-and-white board calibration and region-of-interest extraction, and preprocessing methods including smoothing, differentiation, scale-space, and scattering correction. The feature extraction methods in terms of spectral, spatial, color, and texture were briefly described, and common modeling methods were summarized. Finally, this paper reviewed the research cases of the application of the above methods to the fields of CMM, such as authenticity identification, origin tracing, variety recognition, year identification, sulfur fumigation degree determination, and quantitative measurement.
