Applying generative adversarial network techniques to portable ophthalmic imaging
Eye (Lond)
.
2023 Aug;37(12):2580-2581.
doi: 10.1038/s41433-022-02353-3.
Epub 2022 Dec 12.
Authors
Ethan Waisberg
1
,
Joshua Ong
2
,
Phani Paladugu
3
,
Sharif Amit Kamran
4
,
Nasif Zaman
4
,
Alireza Tavakkoli
4
,
Andrew G Lee
5
6
7
8
9
10
11
12
Affiliations
1
University College Dublin School of Medicine, Belfield, Dublin, Ireland.
2
Michigan Medicine, University of Michigan, Ann Arbor, MI, USA.
3
Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
4
Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada, Reno, Reno, NV, USA.
5
Center for Space Medicine, Baylor College of Medicine, Houston, TX, USA.
[email protected]
.
6
Department of Ophthalmology, Blanton Eye Institute, Houston Methodist Hospital, Houston, TX, USA.
[email protected]
.
7
The Houston Methodist Research Institute, Houston Methodist Hospital, Houston, TX, USA.
[email protected]
.
8
Departments of Ophthalmology, Neurology, and Neurosurgery, Weill Cornell Medicine, New York, NY, USA.
[email protected]
.
9
Department of Ophthalmology, University of Texas Medical Branch, Galveston, TX, USA.
[email protected]
.
10
University of Texas MD Anderson Cancer Center, Houston, TX, USA.
[email protected]
.
11
Texas A&M College of Medicine, Bryan, TX, USA.
[email protected]
.
12
Department of Ophthalmology, The University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
[email protected]
.
PMID:
36509995
PMCID:
PMC10397179
DOI:
10.1038/s41433-022-02353-3
No abstract available
Publication types
Letter
Comment
MeSH terms
Eye
Face*
Head*
Humans
Image Processing, Computer-Assisted