Volume 13 Issue 4
Jul.  2022
Turn off MathJax
Article Contents
LIANG Li. Interpretation on The Consensus Among Chinese Experts About Acquisition and Quality Control of Digital Pathological Images in Cervical Liquid Based Cytology[J]. Medical Journal of Peking Union Medical College Hospital, 2022, 13(4): 571-573. doi: 10.12290/xhyxzz.2022-0100
Citation: LIANG Li. Interpretation on The Consensus Among Chinese Experts About Acquisition and Quality Control of Digital Pathological Images in Cervical Liquid Based Cytology[J]. Medical Journal of Peking Union Medical College Hospital, 2022, 13(4): 571-573. doi: 10.12290/xhyxzz.2022-0100

Interpretation on The Consensus Among Chinese Experts About Acquisition and Quality Control of Digital Pathological Images in Cervical Liquid Based Cytology

doi: 10.12290/xhyxzz.2022-0100
Funds:

Guangzhou R & D Plan in Key Areas 202007040001

More Information
  • Author Bio:

    LIANG Li, E-mail: 2159878@qq.com

  • Received Date: 2022-03-05
  • Accepted Date: 2022-04-21
  • Available Online: 2022-04-28
  • Publish Date: 2022-07-30
  • In order to promote the establishment of standardized digital pathological image-database of cervical liquid-based cytology and the development and application of artificial intelligence-assisted diagnostic products, the first domestic expert consensus in the field of digital pathology namely The consensus among Chinese experts about acquisition and quality control of digital pathological images in cervical liquid-based cytology was published in 2021 and jointly formulated by the group of digital pathology and artificial intelligence of the Association of Chinese Pathologists, the Working Committee of Digital pathology and artificial intelligence of the pathological branch of the Chinese Medical Association, and the group of cell pathology of the Chinese Medical Association. Based on the key contents of the consensus, this paper interprets the relevant issues and looks forward to the future development.
  • loading
  • [1] Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2018, 68: 394-424. doi:  10.3322/caac.21492
    [2] 魏丽惠. 子宫颈癌筛查: 从细胞学检查到HPV检测[J]. 中华妇产科杂志, 2019, 54: 289-292. doi:  10.3760/cma.j.issn.0529-567x.2019.05.001
    [3] 钱丹娟. 薄层液基细胞学检查及HPV检测在子宫颈癌筛查中的应用[J]. 中外医学研究, 2021, 19: 79-81. https://www.cnki.com.cn/Article/CJFDTOTAL-YJZY202110030.htm
    [4] Wang B, He M, Chao A, et al. Cervical cancer screening among adult women in China, 2010[J]. Oncologist, 2015, 20: 627-634. doi:  10.1634/theoncologist.2014-0303
    [5] Tang HP, Cai D, Kong YQ, et al. Cervical cytology screening facilitated by an artificial intelligence microscope: A preli-minary study[J]. Cancer Cytopathol, 2021, 129: 693-700. doi:  10.1002/cncy.22425
    [6] Bao H, Bi H, Zhang X, et al. Artificial intelligence-assisted cytology for detection of cervical intraepithelial neoplasia or invasive cancer: A multicenter, clinical-based, observational study[J]. Gynecol Oncol, 2020, 159: 171-178.
    [7] Bao H, Sun X, Zhang Y, et al. The artificial intelligence-assisted cytology diagnostic system in large-scale cervical cancer screening: A population-based cohort study of 0.7 million women[J]. Cancer Med, 2020, 9: 6896-6906.
    [8] Zhu X, Li X, Ong K, et al. Hybrid AI-assistive diagnostic model permits rapid TBS classification of cervical liquid-based thin-layer cell smears[J]. Nat Commun, 2021, 12: 3541.
    [9] 中国病理医师协会数字病理与人工智能病理学组, 中华医学会病理学分会数字病理与人工智能工作委员会, 中华医学会病理学分会细胞病理学组. 宫颈液基细胞学的数字病理图像采集与图像质量控制中国专家共识[J]. 中华病理学杂志, 2021, 50: 319-322. doi:  10.3760/cma.j.cn112151-20210111-00028
    [10] 朱孝辉, 李晓鸣, 张文丽, 等. 人工智能辅助诊断在宫颈液基薄层细胞学中的应用[J]. 中华病理学杂志, 2021, 50: 333-338. doi:  10.3760/cma.j.cn112151-20201013-00780
    [11] 国家卫生健康委办公厅. 关于印发宫颈癌筛查工作方案和乳腺癌筛查工作方案的通知[EB/OL]. (2022-01-18)[2022-03-05]. http://www.nhc.gov.cn/fys/s3581/202201/cad44d88acca4ae49e12dab9176ae21c.shtml.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (482) PDF downloads(199) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return