Automatic Segment and Quantify Choroid Layer in Myopic eyes: Deep Learning based Model.

Journal: Seminars in ophthalmology
PMID: 35138208

Abstract

PURPOSE: To report a rapid and accurate method based upon deep learning for automatic segmentation and measurement of the choroidal thickness (CT) in myopic eyes, and to determine the relationship between refractive error (RE) and CT.

Authors

  • Chung-Hao Hsiao
    Department of Ophthalmology, Taichung Veterans General Hospital, Taichung, Taiwan.
  • Yu-Len Huang
    Department of Computer science, Tunghai University, Taichung, Taiwan.
  • Siu-Lun Tse
    Department of Computer science, Tunghai University, Taichung, Taiwan.
  • Wei-Ping Hsia
    Department of Ophthalmology, Taichung Veterans General Hospital, Taichung, Taiwan.
  • Hung-Ju Chen
    Department of Ophthalmology, Taichung Veterans General Hospital, Taichung, Taiwan.
  • Yuan-Shao Cheng
    Department of Ophthalmology, Taichung Veterans General Hospital, Taichung, Taiwan.
  • Chia-Jen Chang
    Department of Optometry, Central Taiwan University of Science and Technology, Taichung City, Taiwan.

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