Evaluation of Deep Learning-Based OCTA Denoising in Retinal Vessel Assessment
The N2V2 denoising algorithm can potentially advance the routine clinical use of OCTA by improving the visualization and features quantification.
Authors
- Chenxi Zhang (ORCID: https://orcid.org/0000-0001-9257-1270)
- Kelvin Yi Chong Teo (ORCID: https://orcid.org/0000-0002-7458-7081)
- Zehua Jiang (ORCID: https://orcid.org/0000-0001-9100-0986)
- Chui Ming Gemmy Cheung (ORCID: https://orcid.org/0000-0003-3358-3516)
- Masahiro Akïba (ORCID: https://orcid.org/0000-0002-2735-5763)
- Mohamed Sherif
Institutions
- National University of Singapore (SG)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Singapore National Eye Center (SG)
- Peking Union Medical College Hospital (CN)
- Duke-NUS Medical School (SG)
- Topcon (Japan) (JP)
- Beijing Tsinghua Chang Gung Hospital (CN)
- University of Lausanne (CH)
Publication Details
- Journal
- Translational Vision Science & Technology
- Published
- 2025-12-04
- DOI
- https://doi.org/10.1167/tvst.14.12.10
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00