Diagnosis of Choroidal Disease With Deep Learning-Based Image Enhancement and Volumetric Quantification of Optical Coherence Tomography-Reference-Cited by-同舟云学术

Diagnosis of Choroidal Disease With Deep Learning-Based Image Enhancement and Volumetric Quantification of Optical Coherence Tomography

Published:2022-01-14 Issue:1 Volume:11 Page:22
ISSN:2164-2591
Container-title:Translational Vision Science & Technology
language:en
Short-container-title:Trans. Vis. Sci. Tech.

Author:

Maruyama Kazuichi¹²³,Mei Song⁴,Sakaguchi Hirokazu⁵²,Hara Chikako⁵²,Miki Atsuya⁶²,Mao Zaixing⁴,Kawasaki Ryo¹⁷²,Wang Zhenguo⁴,Sakimoto Susumu²,Hashida Noriyasu²,Quantock Andrew J.⁸,Chan Kinpui⁴,Nishida Kohji²³

Affiliation:

1. Department of Vision Informatics, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan

2. Department of Ophthalmology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan

3. Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Osaka, Japan

4. Topcon Advanced Biomedical Imaging Laboratory, Oakland, New Jersey, USA

5. Department of Advanced Device Medicine, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan

6. Department of Innovative Visual Science, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan

7. Artificial Intelligence Center for Medical Research and Application, Osaka University Hospital, Suita, Osaka, Japan

8. Structural Biophysics Group, School of Optometry and Vision Sciences, College of Biomedical and Life Sciences, Cardiff University, Cardiff, Wales, UK

Publisher

Association for Research in Vision and Ophthalmology (ARVO)

Subject

Ophthalmology,Biomedical Engineering

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