李晓燕, 李晨, 陈灏源, 张勇, 张敬东. 人工智能在结直肠癌数字化病理图像分析中的应用[J]. 协和医学杂志, 2022, 13(4): 542-548. DOI: 10.12290/xhyxzz.2022-0074
引用本文: 李晓燕, 李晨, 陈灏源, 张勇, 张敬东. 人工智能在结直肠癌数字化病理图像分析中的应用[J]. 协和医学杂志, 2022, 13(4): 542-548. DOI: 10.12290/xhyxzz.2022-0074
LI Xiaoyan, LI Chen, CHEN Haoyuan, ZHANG Yong, ZHANG Jingdong. Application and Research Progress of Artificial Intelligence in Digital Pathological Image Analysis of Colorectal Cancer[J]. Medical Journal of Peking Union Medical College Hospital, 2022, 13(4): 542-548. DOI: 10.12290/xhyxzz.2022-0074
Citation: LI Xiaoyan, LI Chen, CHEN Haoyuan, ZHANG Yong, ZHANG Jingdong. Application and Research Progress of Artificial Intelligence in Digital Pathological Image Analysis of Colorectal Cancer[J]. Medical Journal of Peking Union Medical College Hospital, 2022, 13(4): 542-548. DOI: 10.12290/xhyxzz.2022-0074

人工智能在结直肠癌数字化病理图像分析中的应用

Application and Research Progress of Artificial Intelligence in Digital Pathological Image Analysis of Colorectal Cancer

  • 摘要: 计算机人工智能技术在数字病理中应用广泛、发展迅速,是肿瘤精准诊疗时代的一个里程碑。传统病理学作为肿瘤诊断的金标准具有高度主观性及不可重复性,且工作繁琐。基于人工智能技术对数字病理图像进行特征提取及定量分析,并转变为高保真、高通量的可挖掘/分析的数据,在肿瘤早期诊断、分级及构建预后模型等方面表现出独特优势。数字病理人工智能的发展为病理学科带来了难得的机遇,也是精准诊疗的未来发展趋势。本文概述人工智能在结直肠癌数字化病理图像分析中的应用现状和潜在价值,以期为临床诊疗提供参考。

     

    Abstract: The artificial intelligence technology of computer science is widely used in digital pathology and develops rapidly, which is a milestone in the era of accurate diagnosis and treatment of tumors. As the gold standard of tumor diagnosis, traditional pathology is highly subjective and unrepeatable, and the work is cumbersome. Feature extraction and quantitative analysis of digital pathological images based on artificial intelligence technology are transformed into data with high fidelity and high-throughput that can be mined and analyzed. It shows unique advantages in early diagnosis, grading, and constructing the prognostic model of tumors. The development of artificial intelligence in digital pathology has brought a unique opportunity for pathology, and it is also the trend of the development of precise diagnosis and treatment in the future. In order to provide reference for clinical diagnosis and treatment, we review the current status and the value of potential application of artificial intelligence in digital pathological image analysis of colorectal cancer.

     

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