Correlation of choroidal thickness with age in healthy subjects: automatic detection and segmentation using a deep learning model.

Journal: International ophthalmology
PMID: 35381895

Abstract

PROPOSE: The proposed deep learning model with a mask region-based convolutional neural network (Mask R-CNN) can predict choroidal thickness automatically. Changes in choroidal thickness with age can be detected with manual measurements. In this study, we aimed to investigate choroidal thickness in a comprehensive aspect in healthy eyes by utilizing the Mask R-CNN model.

Authors

  • Chen Yu Lin
    Department of Ophthalmology, Taichung Veterans General Hospital, No.1650, Sec. 4, Taiwan Blvd., Situn Dist., Taichung, Taiwan.
  • Yu Len Huang
    Department of Computer Science, Tunghai University, Taichung, Taiwan.
  • Wei Ping Hsia
    Department of Ophthalmology, Taichung Veterans General Hospital, No.1650, Sec. 4, Taiwan Blvd., Situn Dist., Taichung, Taiwan.
  • Yang Wang
    Department of General Surgery The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology Kunming China.
  • Chia Jen Chang
    Department of Ophthalmology, Taichung Veterans General Hospital, No.1650, Sec. 4, Taiwan Blvd., Situn Dist., Taichung, Taiwan. capmchangcj@gmail.com.

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