Development of a deep learning model to detect crystalline retinopathy

Published: 22 December 2022| Version 1 | DOI: 10.17632/mv6khhcg4r.1
Contributor:
TaeKeun Yoo

Description

This study was conducted using a publicly accessible FP database obtained from a previous study perfromed by Cen and additional anonymized FP data. Additional retinal image datasets were extracted from Google Images and Google search engine by searching for following keywords: crystalline retinopathy, talc retinopathy, and retinal crystal deposit. In this study, we aimed of building a deep learning model to detect crystalline retinopathy in FP images.

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Institutions

Yonsei University

Categories

Retinal Disease, Fundus Imaging

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