Intelligent cataract surgery supervision and evaluation via deep learning.

Journal: International journal of surgery (London, England)
PMID:

Abstract

PURPOSE: To assess the performance of a deep learning (DL) algorithm for evaluating and supervising cataract extraction using phacoemulsification with intraocular lens (IOL) implantation based on cataract surgery (CS) videos.

Authors

  • Ting Wang
    CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
  • Jun Xia
    Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China. xiajun2003sz@aliyun.com.
  • Ruiyang Li
    2State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong China.
  • Ruixin Wang
    State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.
  • Nick Stanojcic
    Department of Ophthalmology, St. Thomas' Hospital, London, United Kingdom.
  • Ji-Peng Olivia Li
    Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom.
  • Erping Long
    State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Xian Lie South Road 54#, Guangzhou, 510060, China.
  • Jinghui Wang
    Shanxi Entry-Exit Inspection and Quarantine Bureau, Taiyuan, China.
  • Xiayin Zhang
    State Key Laboratory of Ophthalmology, Clinical Research Center for Ocular Disease, Zhongshan Ophthalmic Centre, Sun Yat-sen University, Guangzhou, China.
  • Jianbin Li
    Medical Molecular Biology, Beijing Institute of Biotechnology, Beijing, People's Republic of China.
  • Xiaohang Wu
    State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Xian Lie South Road 54#, Guangzhou, 510060, China.
  • Zhenzhen Liu
    Department of Functional Science, School of Medicine, Yangtze University, No.1 Nanhuan Road, Jingzhou City 434100, China.
  • Jingjing Chen
    Department of Cardiovascular Medicine, Affiliated Hospital of Guizhou Medical University, Guiyang, China.
  • Hui Chen
    Xiangyang Central HospitalAffiliated Hospital of Hubei University of Arts and Science Xiangyang 441000 China.
  • Danyao Nie
    Shenzhen Eye Hospital, Shenzhen Key Laboratory of Ophthalmology, Shenzhen University School of Medicine, Shenzhen, China.
  • Huanqi Ni
    School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China.
  • Ruoxi Chen
    School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China.
  • Wenben Chen
    State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Vision Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, Guangdong, China.
  • Shiyi Yin
    Department of Ophthalmology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
  • Duru Lin
    State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Vision Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, Guangdong, China.
  • Pisong Yan
    State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.
  • Zeyang Xia
    Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, ShenZhen, China.
  • Shengzhi Lin
    Guangzhou Oculotronics Medical Instrument Co., Ltd, Guangzhou, China.
  • Kai Huang
  • Haotian Lin
    State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou.