Deep Learning-Based Model for Automatic Assessment of Anterior Angle Chamber in Ultrasound Biomicroscopy.

Journal: Ultrasound in medicine & biology
PMID: 37730479

Abstract

OBJECTIVE: The goal of the work described here was to develop and assess a deep learning-based model that could automatically segment anterior chamber angle (ACA) tissues; classify iris curvature (I-Curv), iris root insertion (IRI), and angle closure (AC); automatically locate scleral spur; and measure ACA parameters in ultrasound biomicroscopy (UBM) images.

Authors

  • Weiyan Jiang
    Eye Center, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, China.
  • Yulin Yan
    Department of Ophthalmology, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, China.
  • Simin Cheng
    Eye Center, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, China.
  • Shanshan Wan
    Department of Ophthalmology, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, China.
  • Linying Huang
    Eye Center, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, China.
  • Hongmei Zheng
    Eye Center, Renmin Hospital of Wuhan University, Wuhan, China.
  • Miao Tian
    Department of Ophthalmology, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, China.
  • Jian Zhu
  • Yumiao Pan
    Eye Center, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, China.
  • Jia Li
    Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Zhongshan Tsuihang New District, Guangdong, 528400, PR China; School of Pharmacy, Zunyi Medical University, Zunyi, 563000, PR China; National Center for Drug Screening, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, PR China.
  • Li Huang
    National Research Center for Resettlement (NRCR), Hohai University, 1 Xikang Road, Nanjing 210098, China. lily8214@hhu.edu.cn.
  • Lianlian Wu
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China.
  • Yuelan Gao
    Department of Ophthalmology, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, China.
  • Jiewen Mao
    Eye Center, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, China.
  • Yuyu Cong
    Eye Center, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, China.
  • Yujin Wang
    Eye Center, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, China.
  • Qian Deng
    Eye Center, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, China.
  • Xiaoshuo Shi
    Department of Stomatology, Affiliated Hospital of Hebei University, Baoding, Hebei 071000, P. R. China.
  • Zixian Yang
    Eye Center, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, China.
  • Siqi Liu
    National University of Singapore Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore.
  • Biqing Zheng
    Wuhan EndoAngel Medical Technology Company, Wuhan, China.
  • Yanning Yang
    Department of Ophthalmology, Renmin Hospital of Wuhan University, 99 Zhangzhidong Road, Wuhan, 430060, Hubei Province, China. ophyyn@163.com.

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