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  • 陈颖,魏培莲,潘军,周洁,董昌盛,于观贞.数字化全玻片助力人工智能病理图像决策[J].第二军医大学学报,2018,39(8):840-845    [点击复制]
  • CHEN Ying,WEI Pei-lian,PAN Jun,ZHOU Jie,DONG Chang-sheng,YU Guan-zhen.Digital whole slide helps artificial intelligence in pathological imaging strategies[J].Acad J Sec Mil Med Univ,2018,39(8):840-845   [点击复制]
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数字化全玻片助力人工智能病理图像决策
陈颖1,魏培莲2,潘军3,周洁2,董昌盛2,于观贞2*
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(1. 海军军医大学(第二军医大学)长海医院病理科, 上海 200433;
2. 上海中医药大学附属龙华医院肿瘤七科, 上海 200032;
3. 解放军81医院全军肿瘤中心肿瘤内科, 南京 210002
*通信作者)
摘要:
基于病理切片图像的人工智能技术促进了医学发展,而病理人工智能技术的发展得益于数字化全玻片。全玻片数字化能提供大量可任意放大和方便标注的数据,利于深度学习,极易临床推广应用。数字化全玻片不仅可应用于人体病理,其在动物和植物病理方面也可发挥重要作用。本文系统性探讨了数字化全玻片结合人工智能技术在病理识别、特征提取、动物模型和植物形态学方面的应用潜力,旨在为数字病理的临床实践提供新的思维方式。
关键词:  人工智能  数字化全玻片  中草药  动物模型
DOI:10.16781/j.0258-879x.2018.08.0840
投稿时间:2018-06-21修订日期:2018-07-16
基金项目:国家自然科学基金(81572856),上海中医药大学附属龙华医院高层次人才引进项目(LH02.51.002).
Digital whole slide helps artificial intelligence in pathological imaging strategies
CHEN Ying1,WEI Pei-lian2,PAN Jun3,ZHOU Jie2,DONG Chang-sheng2,YU Guan-zhen2*
(1. Department of Pathology, Changhai Hospital, Navy Medical University(Second Military Medical University), Shanghai 200433, China;
2. Department of Oncology(Ⅶ), Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China;
3. Department of Medical Oncology, Cancer Center of PLA, No. 81 Hospital of PLA, Nanjing 210002, Jiangsu, China
*Corresponding author)
Abstract:
Artificial intelligence technology based on pathological slice images promotes the development of medicine, and the development of artificial intelligence technology in pathological imaging benefits from the digital whole slide. The digitization of whole slide can provide a large amount of data that can be freely amplified and conveniently labeled, which is conducive to deep learning and clinical application. Digital whole slide is not only applied to human pathology, but also to animal and plant pathology. In this paper, we systematically discussed the role of digital whole slide combined with artificial intelligence technology in pathological recognition, feature extraction, animal models and plant morphology, aiming to provide new clues for the clinical practice of digital pathology.
Key words:  artificial intelligence  digital whole slide  Chinese herbal drugs  animal models