Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review

被引:90
作者
Fenner, Beau J. [1 ]
Wong, Raymond L. M. [2 ]
Lam, Wai-Ching [3 ]
Tan, Gavin S. W. [4 ,5 ,6 ]
Cheung, Gemmy C. M. [5 ,6 ,7 ]
机构
[1] Singapore Natl Eye Ctr, Residency Program, Singapore, Singapore
[2] Chinese Univ Hong Kong, Dept Ophthalmol & Visual Sci, Hong Kong, Peoples R China
[3] Univ Hong Kong, Dept Ophthalmol, Shatin, Hong Kong, Peoples R China
[4] Singapore Natl Eye Ctr, Surg Retina Dept, Singapore, Singapore
[5] Duke NUS Grad Med Sch, Ophthlamol & Visual Sci Acad Clin Program, Singapore, Singapore
[6] Singapore Eye Res Inst, Retina Res Grp, Singapore, Singapore
[7] Singapore Natl Eye Ctr, Med Retina Dept, Singapore, Singapore
关键词
Artificial intelligence; Deep learning; Diabetic retinopathy; Optical coherence tomography; Retina; Ultrawide field imaging; COHERENCE TOMOGRAPHY ANGIOGRAPHY; FUNDUS PHOTOGRAPHY; MACULAR EDEMA; COST-EFFECTIVENESS; PERIPHERAL LESIONS; RISK-FACTORS; PREVALENCE; PROGRAM; TELEMEDICINE; SMARTPHONE;
D O I
10.1007/s40123-018-0153-7
中图分类号
R77 [眼科学];
学科分类号
100212 ;
摘要
Rising prevalence of diabetes worldwide has necessitated the implementation of population-based diabetic retinopathy (DR) screening programs that can perform retinal imaging and interpretation for extremely large patient cohorts in a rapid and sensitive manner while minimizing inappropriate referrals to retina specialists. While most current screening programs employ mydriatic or nonmydriatic color fundus photography and trained image graders to identify referable DR, new imaging modalities offer significant improvements in diagnostic accuracy, throughput, and affordability. Smartphone-based fundus photography, macular optical coherence tomography, ultrawide-field imaging, and artificial intelligence-based image reading address limitations of current approaches and will likely become necessary as DR becomes more prevalent. Here we review current trends in imaging for DR screening and emerging technologies that show potential for improving upon current screening approaches.
引用
收藏
页码:333 / 346
页数:14
相关论文
共 96 条
[1]   Web-based screening for diabetic retinopathy in a primary care population: The EyeCheck project [J].
Abramoff, MD ;
Suttorp-Schulten, MSA .
TELEMEDICINE JOURNAL AND E-HEALTH, 2005, 11 (06) :668-674
[2]   Improved Automated Detection of Diabetic Retinopathy on a Publicly Available Dataset Through Integration of Deep Learning [J].
Abramoff, Michael David ;
Lou, Yiyue ;
Erginay, Ali ;
Clarida, Warren ;
Amelon, Ryan ;
Folk, James C. ;
Niemeijer, Meindert .
INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2016, 57 (13) :5200-5206
[3]   RETINAL VASCULAR PERFUSION DENSITY MAPPING USING OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY IN NORMALS AND DIABETIC RETINOPATHY PATIENTS [J].
Agemy, Steven A. ;
Scripsema, Nicole K. ;
Shah, Chirag M. ;
Chui, Toco ;
Garcia, Patricia M. ;
Lee, Jessica G. ;
Gentile, Ronald C. ;
Hsiao, Yi-Sing ;
Zhou, Qienyuan ;
Ko, Tony ;
Rosen, Richard B. .
RETINA-THE JOURNAL OF RETINAL AND VITREOUS DISEASES, 2015, 35 (11) :2353-2363
[4]  
Aiello L M, 1998, J Am Optom Assoc, V69, P699
[5]   Diabetic retinopathy [J].
Aiello, LP ;
Gardner, TW ;
King, GL ;
Blankenship, G ;
Cavallerano, JD ;
Ferris, FL ;
Klein, R .
DIABETES CARE, 1998, 21 (01) :143-156
[6]  
[Anonymous], 1981, OPHTHALMOLOGY, V88, P583
[7]  
[Anonymous], 1991, Ophthalmology, V98, P786
[8]  
[Anonymous], J OPHTHALMIC PHOTOGR
[9]  
[Anonymous], 2015, Eur. Ophthalmic Rev, DOI DOI 10.17925/EOR.2015.09.01.49
[10]  
Backlund LB, 1997, DIABETIC MED, V14, P732, DOI 10.1002/(SICI)1096-9136(199709)14:9<732::AID-DIA474>3.0.CO