한빛사
>
한빛사논문
한빛사논문
- 조회21
Aaron Y LeeAaron Y Lee
University of Washington
Prog. Retin. Eye Res., May 11 2025, S1350-9462(25)00036-9 | https://doi.org/10.1016/j.preteyeres.2025.101363
The March to Harmonized Imaging Standards for Retinal Imaging
Nayoon Gim 1,2,3,4,#, Alina N. Ferguson BS 1,2,3,#, Marian Blazes MD 1,2, Cecilia S. Lee MD, MS 1,2, Aaron Y. Lee MD, MSCI 1,2
1Department of Ophthalmology, University of Washington, Seattle, Washington
2Roger and Angie Karalis Johnson Retina Center, Seattle, Washington
3University of Washington School of Medicine, Seattle, Washington
4Department of Bioengineering, University of Washington, Seattle, Washington
#The authors contributed equally to this work and should be considered co-first authors.
Corresponding author: Aaron Y. Lee
1Department of Ophthalmology, University of Washington, Seattle, Washington
2Roger and Angie Karalis Johnson Retina Center, Seattle, Washington
3University of Washington School of Medicine, Seattle, Washington
4Department of Bioengineering, University of Washington, Seattle, Washington
#The authors contributed equally to this work and should be considered co-first authors.
Corresponding author: Aaron Y. Lee
Abstract
The adoption of standardized imaging protocols in retinal imaging is critical to overcoming challenges posed by fragmented data formats across devices and manufacturers. The lack of standardization hinders clinical interoperability, collaborative research, and the development of artificial intelligence (AI) models that depend on large, high-quality datasets. The Digital Imaging and Communication in Medicine (DICOM) standard offers a robust solution for ensuring interoperability in medical imaging. Although DICOM is widely utilized in radiology and cardiology, its adoption in ophthalmology remains limited. Retinal imaging modalities such as optical coherence tomography (OCT), fundus photography, and OCT angiography (OCTA) have revolutionized retinal disease management but are constrained by proprietary and non-standardized formats. This review underscores the necessity for harmonized imaging standards in ophthalmology, detailing DICOM standards for retinal imaging including ophthalmic photography (OP), OCT, and OCTA, and their requisite metadata information. Additionally, the potential of DICOM standardization for advancing AI applications in ophthalmology is explored. A notable example is the Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI) dataset, the first publicly available standards-compliant DICOM retinal imaging dataset. This dataset encompasses diverse retinal imaging modalities, including color fundus photography, infrared, autofluorescence, OCT, and OCTA. By leveraging multimodal retinal imaging, AI-READI provides a transformative resource for studying diabetes and its complications, setting a blueprint for future datasets aimed at harmonizing imaging formats and enabling AI-driven breakthroughs in ophthalmology. Our manuscript also addresses challenges in retinal imaging for diabetic patients, retinal imaging-based AI applications for studying diabetes, and potential advancements in retinal imaging standardization.
논문정보
- Review Paper
- 2025년 05월 (BRIC 등록일 2025-05-30)
- 국외 연구진
댓글 작성 로그인
팝업 닫기관련 링크
