Fovea localization neural network for multimodal retinal imaging

Cheolhong An; Yiqian Wang; Junkang Zhang; Dirk-Uwe G. Bartsch; William R. Freeman

doi:10.1117/12.2569858

20 August 2020 Fovea localization neural network for multimodal retinal imaging

Cheolhong An, Yiqian Wang, Junkang Zhang, Dirk-Uwe G. Bartsch, William R. Freeman

Author Affiliations +

Proceedings Volume 11511, Applications of Machine Learning 2020; 1151111 (2020) https://doi.org/10.1117/12.2569858
Event: SPIE Optical Engineering + Applications, 2020, Online Only

Abstract

The fovea is one of the most significant regions of the human eye. Accurate localization of the fovea is very helpful to downstream computer-aided diagnosis analysis in retinal imaging. Most previous researches have focused on fovea localization for the color fundus imaging. In this paper, we propose a three-step process to localize the foveal center and the foveal region for three retinal modalities: color fundus, Infrared (IR), and optical coherence tomography (OCT). From the experimental results, the proposed method achieves accurate fovea localization for multimodal imaging.

Citation Download Citation

Cheolhong An, Yiqian Wang, Junkang Zhang, Dirk-Uwe G. Bartsch, and William R. Freeman "Fovea localization neural network for multimodal retinal imaging", Proc. SPIE 11511, Applications of Machine Learning 2020, 1151111 (20 August 2020); https://doi.org/10.1117/12.2569858

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