Multimodality semisupervised learning for ophthalmic biomarkers detection

Yanming Chen; Chenxi Niu; Chen Ye; Shengji Jin; Yue Li; Chi Xu; Keyi Liu; Haowei Gao; Jingxi Hu; Yuanhao Zou; Huizhong Zheng; Xiangjian He

doi:10.1117/12.3019655

2 May 2024 Multimodality semisupervised learning for ophthalmic biomarkers detection

Yanming Chen, Chenxi Niu, Chen Ye, Shengji Jin, Yue Li, Chi Xu, Keyi Liu, Haowei Gao, Jingxi Hu, Yuanhao Zou, Huizhong Zheng, Xiangjian He

Author Affiliations +

Proceedings Volume 13164, International Workshop on Advanced Imaging Technology (IWAIT) 2024; 1316433 (2024) https://doi.org/10.1117/12.3019655
Event: International Workshop on Advanced Imaging Technology (IWAIT) 2024, 2024, Langkawi, Malaysia

Abstract

Ophthalmic Biomarkers, as an objective and quantifiable approach to identifying the ophthalmological disease process, are proven to be useful not only in assisting healthcare professionals in disease diagnosis but also in the identification of phenomena and risk factors in the early stages, which greatly contribute to disease prevention and better treatment of patients. In this study, a deep learning method is introduced to achieve simultaneous automatic recognition of six prevalent ophthalmic biomarkers in the OLIVES dataset. To enhance identification accuracy, semi-supervised learning techniques are adopted in this research and different data modalities are jointly optimized using a guided loss function. The experimental results reveal that the method reaches an F1 score of 0.70 on a test set with 3,872 images.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yanming Chen, Chenxi Niu, Chen Ye, Shengji Jin, Yue Li, Chi Xu, Keyi Liu, Haowei Gao, Jingxi Hu, Yuanhao Zou, Huizhong Zheng, and Xiangjian He "Multimodality semisupervised learning for ophthalmic biomarkers detection", Proc. SPIE 13164, International Workshop on Advanced Imaging Technology (IWAIT) 2024, 1316433 (2 May 2024); https://doi.org/10.1117/12.3019655

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