1. |
Novais EA, Baumal CR, Sarraf D, et al. Multimodal imaging in retinal disease: a consensus definition[J]. Ophthalmic Surg Lasers Imaging Retina, 2016, 47(3): 201-205. DOI: 10.3928/23258160-20160229-01.
|
2. |
Choudhry N, Duker JS, Freund KB, et al. Classification and guidelines for widefield imaging: recommendations from the International Widefield Imaging Study Group[J]. Ophthalmol Retina, 2019, 3(10): 843-849. DOI: 10.1016/j.oret.2019.05.007.
|
3. |
Moriyama M, Cao K, Ogata S, et al. Detection of posterior vortex veins in eyes with pathologic myopia by ultra-widefield indocyanine green angiography[J]. Br J Ophthalmol, 2017, 101(9): 1179-1184. DOI: 10.1136/bjophthalmol-2016-309877.
|
4. |
Hirahara S, Yasukawa T, Kominami A, et al. Densitometry of choroidal vessels in eyes with and without central serous chorioretinopathy by wide-field indocyanine green angiography[J]. Am J Ophthalmol, 2016, 166: 103-111. DOI: 10.1016/j.ajo.2016.03.040.
|
5. |
Fujimoto J, Swanson E. The development, commercialization, and impact of optical coherence tomography[J]. Invest Ophthalmol Vis Sci, 2016, 57(9): OCT1-OCT13. DOI: 10.1167/iovs.16-19963.
|
6. |
Duncker T, Marsiglia M, Lee W, et al. Correlations among near-infrared and short-wavelength autofluorescence and spectral-domain optical coherence tomography in recessive Stargardt disease[J]. Invest Ophthalmol Vis Sci, 2014, 55(12): 8134-8143. DOI: 10.1167/iovs.14-14848.
|
7. |
Mrejen S, Khan S, Gallego-Pinazo R, et al. Acute zonal occult outer retinopathy: a classification based on multimodal imaging[J]. JAMA Ophthalmol, 2014, 132(9): 1089-1098. DOI: 10.1001/jamaophthalmol.2014.1683.
|
8. |
范文强, 王志臣, 陈宝刚, 等. 自适应光学相干层析在视网膜高分辨成像中的应用[J]. 红外与激光工程, 2020, 49(10): 58-70. DOI: 10.3788/IRLA20200333.Fan WQ, Wang ZC, Chen BG, et al. Application of adaptive optics coherence tomography in retinal high resolution imaging[J]. Infrared and Laser Engineering, 2020, 49(10): 58-70. DOI: 10.3788/IRLA20200333.
|
9. |
Wynne N, Carroll J, Duncan JL. Promises and pitfalls of evaluating photoreceptor-based retinal disease with adaptive optics scanning light ophthalmoscopy (AOSLO)[J/OL]. Prog Retin Eye Res, 2021, 83: 100920[2020-11-06]. https://pubmed.ncbi.nlm.nih.gov/33161127/. DOI: 10.1016/j.preteyeres.2020.100920.
|
10. |
Dysli C, Wolf S, Berezin MY, et al. Fluorescence lifetime imaging ophthalmoscopy[J]. Prog Retin Eye Res, 2017, 60: 120-143. DOI: 10.1016/j.preteyeres.2017.06.005.
|
11. |
Dysli C, Quellec G, Abegg M, et al. Quantitative analysis of fluorescence lifetime measurements of the macula using the fluorescence lifetime imaging ophthalmoscope in healthy subjects[J]. Invest Ophthalmol Vis Sci, 2014, 55(4): 2106-2113. DOI: 10.1167/iovs.13-13627.
|
12. |
Dysli C, Berger L, Wolf S, et al. Fundus autofluorescence lifetimes and central serous chorrioretinopathy[J]. Retina, 2017, 37(11): 2151-2161. DOI: 10.1097/IAE.0000000000001452.
|
13. |
Chandran K, Shenoy SB, Kulkarni C, et al. Bilateral simultaneous central retinal artery occlusion (CRAO) in a patient with systemic lupus erythematosus (SLE)[J/OL]. Am J Ophthalmol Case Rep, 2020, 19: 100833[2020-07-20]. https://pubmed.ncbi.nlm.nih.gov/32904183/. DOI: 10.1016/j.ajoc.2020.100833.
|
14. |
Ruggeri A, Poletti E, Fiorin D, et al. From laboratory to clinic: the development of web-based tools for the estimation of retinal diagnostic parameters[J]. Annu Int Conf IEEE Eng Med Biol Soc, 2011, 2011: 3379-3382. DOI: 10.1109/IEMBS.2011.6090915.
|
15. |
Fiorin D, Ruggeri A. Computerized analysis of narrow-field ROP images for the assessment of vessel caliber and tortuosity[J]. Annu Int Conf IEEE Eng Med Biol Soc, 2011, 2011: 2622-2625. DOI: 10.1109/IEMBS.2011.6090723.
|
16. |
Zekavat SM, Raghu VK, Trinder M, et al. Deep learning of the retina enables phenome-and genome-wide analyses of the microvasculature[J]. Circulation, 2022, 145(2): 134-150. DOI: 10.1161/CIRCULATIONAHA.121.057709.
|
17. |
陈有信, 张碧磊, 张弘哲. 眼科人工智能技术的现状与问题[J]. 中华眼底病杂志, 2019, 35(2): 119-123. DOI: 10.3760/cma.j.issn.1005-1015.2019.02.003.Chen YX, Zhang BL, Zhang HZ. Insights and prospectives of ophthalmologic artificial intelligence technology[J]. Chin J Ocul Fundus Dis, 2019, 35(2): 119-123. DOI: 10.3760/cma.j.issn.1005-1015.2019.02.003.
|
18. |
Ryu G, Lee K, Park D, et al. A deep learning model for identifying diabetic retinopathy using optical coherence tomography angiography[J/OL]. Sci Rep, 2021, 11(1): 23024[2021-11-26]. https://pubmed.ncbi.nlm.nih.gov/34837030/. DOI: 10.1038/s41598-021-02479-6.
|
19. |
Lin D, Xiong J, Liu C, et al. Application of comprehensive artificial intelligence retinal expert (CARE) system: a national real-world evidence study[J/OL]. Lancet Digit Health, 2021, 3(8): e486-e495[2021-08-01]. https://pubmed.ncbi.nlm.nih.gov/34325853/. DOI: 10.1016/S2589-7500(21)00086-8.
|