人工智能结合光谱诊断技术在肺癌组织鉴别领域的应用与研究进展

doi:10.3969/j.issn.1006-7795.2023.06.028

摘要/Abstract

摘要： 对现今光谱技术在肺癌组织鉴别领域的相关研究以及人工智能的应用进行系统综述，以阐明人工智能结合光谱诊断技术在临床中的应用价值和发展方向。使用特定策略对Pubmed数据库和中国知网数据库进行检索，总结在病理诊断领域表现较佳的光谱技术，并进行简要对比。当前主流的光谱技术为高光谱成像、漫反射光谱、拉曼光谱、荧光光谱和多光谱技术，人工智能可以进一步增强光谱技术的诊断效能。人工智能结合光谱诊断有实现即时鉴别肺癌浸润程度的潜力，但当前多数研究还停留在肿瘤良恶性鉴别和确定肿瘤边界阶段。

关键词: 肺癌, 人工智能, 光谱技术, 快速诊断

Abstract: To systematically review the current research on spectral technology in the identification of lung cancer tissues and the application of artificial intelligence, to clarify the clinical application value and development direction of artificial intelligence combined with spectral diagnosis technology. Pubmed and CNKI databases were searched via using a specific strategy, and the better performing spectral techniques in the field of pathological diagnosis were summarized and briefly compared. The current mainstream spectral techniques include hyperspectral imaging, diffuse reflectance spectroscopy, Raman spectroscopy, fluorescence spectroscopy, and multispectral techniques.Artificial intelligence can further enhance the diagnostic performance of spectral techniques. Artificial intelligence combined with spectral diagnosis has the potential to realize the instant differentiation of lung cancer invasion degree, but most of the current research is still at the stage of differentiating benign and malignant tumors and determining the tumor boundary.

Key words: lung cancer, artificial intelligence, spectral technology, rapid diagnosis

中图分类号:

R734.2

罗艺, 秦齐, 王沛豪, 郭康顺, 张鑫平, 崔永. 人工智能结合光谱诊断技术在肺癌组织鉴别领域的应用与研究进展[J]. 首都医科大学学报, 2023, 44(6): 1095-1102.

Luo Yi, Qin Qi, Wang Peihao, Guo Kangshun, Zhang Xinping, Cui Yong. Application and research progress of artificial intelligence combined with spectral diagnosis technology in the identification of lung cancer tissues[J]. Journal of Capital Medical University, 2023, 44(6): 1095-1102.

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