Automated detection of crystalline retinopathy via fundus photography using multistage generative adversarial networks-Reference-Cited by-同舟云学术

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Automated detection of crystalline retinopathy via fundus photography using multistage generative adversarial networks

Published:2023-10 Issue:4 Volume:43 Page:725-735
ISSN:0208-5216
Container-title:Biocybernetics and Biomedical Engineering
language:en
Short-container-title:Biocybernetics and Biomedical Engineering

Author:

Young Choi Eun,Han Seung Hoon,Hee Ryu Ik,Kuk Kim Jin,Sik Lee In,Han Eoksoo,Kim Hyungsu,Yul Choi Joon,Keun Yoo Tae

Funder

National Research Foundation of Korea

Ministry of Education

Publisher

Elsevier BV

Subject

Biomedical Engineering

Reference56 articles.

1. Insights into systemic disease through retinal imaging-based oculomics;Wagner;Trans Vis Sci Tech,2020

2. Systemic considerations in the management of diabetic retinopathy;Aiello;Am J Ophthalmol,2001

3. The role of big data analysis in identifying a relationship between glaucoma and diabetes mellitus;Oh;Ann Transl Med,2022

4. An algorithm to identify the aetiology of crystalline retinopathy;Pereira;Clin Exp Optom,2019

5. Crystalline retinopathy and optical coherence tomography angiography: new insights in pathogenesis;Kovach;Ann Eye Sci,2020

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhancing Cataract Detection through Hybrid CNN Approach and Image Quadration: A Solution for Precise Diagnosis and Improved Patient Care;Electronics;2024-06-15

2. A feasibility study on the adoption of a generative denoising diffusion model for the synthesis of fundus photographs using a small dataset;Discover Applied Sciences;2024-04-03

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