Advanced color fundus photography using deep learning for screening glaucoma in low resource setting

Hyunmo Yang; Yujin Ahn; Joon S. You; Sang Woo Kim; WoongGyu Jung

doi:10.1117/12.2610466

7 March 2022 Advanced color fundus photography using deep learning for screening glaucoma in low resource setting

Hyunmo Yang, Yujin Ahn, Joon S. You, Sang Woo Kim, WoongGyu Jung

Author Affiliations +

Proceedings Volume PC11950, Optics and Biophotonics in Low-Resource Settings VIII; PC119500F (2022) https://doi.org/10.1117/12.2610466
Event: SPIE BiOS, 2022, San Francisco, California, United States

Abstract

We introduce an advanced color fundus photography using deep learning (DL) architecture for screening glaucoma in low resource setting. The proposed DL architecture is based on a convolutional neural network and trained using clinical image data from color fundus photography and optical coherence tomography. Customized hand-held device integrated with DL model detect and quantify glaucomatous damage in fundus photograph. In validation study, our approach improves the screening capability which cannot be achieved by retinal fundus photography alone. This low-cost handy device with fast-feedback software would be very adequate tool to screen glaucoma in low resource setting.

Conference Presentation

Citation Download Citation

Hyunmo Yang, Yujin Ahn, Joon S. You, Sang Woo Kim, and WoongGyu Jung "Advanced color fundus photography using deep learning for screening glaucoma in low resource setting", Proc. SPIE PC11950, Optics and Biophotonics in Low-Resource Settings VIII, PC119500F (7 March 2022); https://doi.org/10.1117/12.2610466

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