-
3
-
-
85044554179
-
Surveillance of sight loss due to delay in ophthalmic treatment or review: frequency, cause and outcome
-
PID: 28128796
-
Foot, B. & MacEwen, C. Surveillance of sight loss due to delay in ophthalmic treatment or review: frequency, cause and outcome. Eye 31, 771–775 (2017)
-
(2017)
Eye
, vol.31
, pp. 771-775
-
-
Foot, B.1
MacEwen, C.2
-
4
-
-
84860218671
-
The estimated prevalence and incidence of late stage age related macular degeneration in the UK
-
PID: 22329913
-
Owen, C. G. et al. The estimated prevalence and incidence of late stage age related macular degeneration in the UK. Br. J. Ophthalmol. 96, 752–756 (2012)
-
(2012)
Br. J. Ophthalmol.
, vol.96
, pp. 752-756
-
-
Owen, C.G.1
-
5
-
-
84930753511
-
Incidence of late-stage age-related macular degeneration in American whites: systematic review and meta-analysis
-
PID: 25857680
-
Rudnicka, A. R. et al. Incidence of late-stage age-related macular degeneration in American whites: systematic review and meta-analysis. Am. J. Ophthalmol. 160, 85–93 (2015)
-
(2015)
Am. J. Ophthalmol.
, vol.160
, pp. 85-93
-
-
Rudnicka, A.R.1
-
6
-
-
85026628989
-
Magnitude, temporal trends, and projections of the global prevalence of blindness and distance and near vision impairment: a systematic review and meta-analysis
-
PID: 28779882
-
Bourne, R. R. A. et al. Magnitude, temporal trends, and projections of the global prevalence of blindness and distance and near vision impairment: a systematic review and meta-analysis. Lancet Glob. Health 5, e888–e897 (2017)
-
(2017)
Lancet Glob. Health
, vol.5
, pp. e888-e897
-
-
Bourne, R.R.A.1
-
7
-
-
85044561343
-
A view of the current and future role of optical coherence tomography in the management of age-related macular degeneration
-
PID: 27886184
-
Schmidt-Erfurth, U., Klimscha, S., Waldstein, S. M. & Bogunović, H. A view of the current and future role of optical coherence tomography in the management of age-related macular degeneration. Eye 31, 26–44 (2017)
-
(2017)
Eye
, vol.31
, pp. 26-44
-
-
Schmidt-Erfurth, U.1
Klimscha, S.2
Waldstein, S.M.3
Bogunović, H.4
-
8
-
-
85007529863
-
Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs
-
Gulshan, V. et al. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. J. Am. Med. Assoc. 316, 2402–2410 (2016)
-
(2016)
J. Am. Med. Assoc.
, vol.316
, pp. 2402-2410
-
-
Gulshan, V.1
-
9
-
-
85016143105
-
Dermatologist-level classification of skin cancer with deep neural networks
-
PID: 28117445
-
Esteva, A. et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature 542, 115––118 (2017)
-
(2017)
Nature
, vol.542
, pp. 115-118
-
-
Esteva, A.1
-
10
-
-
0026254046
-
Optical coherence tomography
-
PID: 1957169
-
Huang, D. et al. Optical coherence tomography. Science 254, 1178–1181 (1991)
-
(1991)
Science
, vol.254
, pp. 1178-1181
-
-
Huang, D.1
-
11
-
-
85033476665
-
How to defuse a demographic time bomb: the way forward?
-
PID: 28622310
-
Buchan, J. C. et al. How to defuse a demographic time bomb: the way forward? Eye 31, 1519–1522 (2017)
-
(2017)
Eye
, vol.31
, pp. 1519-1522
-
-
Buchan, J.C.1
-
12
-
-
32444440211
-
A modeled economic analysis of a digital teleophthalmology system as used by three federal healthcare agencies for detecting proliferative diabetic retinopathy
-
PID: 16430383
-
Whited, J. D. et al. A modeled economic analysis of a digital teleophthalmology system as used by three federal healthcare agencies for detecting proliferative diabetic retinopathy. Telemed. J. E Health 11, 641–651 (2005)
-
(2005)
Telemed. J. E Health
, vol.11
, pp. 641-651
-
-
Whited, J.D.1
-
13
-
-
84951834022
-
U-Net: Convolutional networks for biomedical image segmentation
-
Navab N., Hornegger J., Wells W., Frangi A., Springer, Cham, Switzerland
-
Ronneberger, O., Fischer, P. & Brox, T. U-Net: convolutional networks for biomedical image segmentation. in Navab N., Hornegger J., Wells W., Frangi A. (eds.) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015. MICCAI 2015. Lecture Notes in Computer Science, vol. 9351 (Springer, Cham, Switzerland, 2015)
-
(2015)
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015. MICCAI 2015. Lecture Notes in Computer Science
, vol.9351
-
-
Ronneberger, O.1
Fischer, P.2
Brox, T.3
-
14
-
-
84996483314
-
3D U-Net: Learning dense volumetric segmentation from sparse annotation
-
Ourselin, S., Joskowicz, L., Sabuncu, M., Unal, G., Wells, W, Springer, Cham, Switzerland
-
Çiçek, Ö., Abdulkadir, A., Lienkamp, S. S., Brox, T. & Ronneberger, O. 3D U-Net: learning dense volumetric segmentation from sparse annotation. in Ourselin, S., Joskowicz, L., Sabuncu, M., Unal, G., Wells, W. (eds.) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016. MICCAI 2016. Lecture Notes in Computer Science, vol. 9901 (Springer, Cham, Switzerland; 2016)
-
(2016)
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016. MICCAI 2016. Lecture Notes in Computer Science
, vol.9901
-
-
Çiçek, Ö.1
Abdulkadir, A.2
Lienkamp, S.S.3
Brox, T.4
Ronneberger, O.5
-
15
-
-
79955590384
-
Delay between medical indication to anti-VEGF treatment in age-related macular degeneration can result in a loss of visual acuity
-
PID: 20865421
-
Muether, P. S., Hermann, M. M., Koch, K. & Fauser, S. Delay between medical indication to anti-VEGF treatment in age-related macular degeneration can result in a loss of visual acuity. Graefes Arch. Clin. Exp. Ophthalmol. 249, 633–637 (2011)
-
(2011)
Graefes Arch. Clin. Exp. Ophthalmol.
, vol.249
, pp. 633-637
-
-
Muether, P.S.1
Hermann, M.M.2
Koch, K.3
Fauser, S.4
-
16
-
-
60149107965
-
Delay in treating age-related macular degeneration in Spain is associated with progressive vision loss
-
PID: 18202712
-
Arias, L. et al. Delay in treating age-related macular degeneration in Spain is associated with progressive vision loss. Eye 23, 326–333 (2009)
-
(2009)
Eye
, vol.23
, pp. 326-333
-
-
Arias, L.1
-
17
-
-
85011554665
-
Transfer learning based classification of optical coherence tomography images with diabetic macular edema and dry age-related macular degeneration
-
PID: 28270969
-
Karri, S. P. K., Chakraborty, D. & Chatterjee, J. Transfer learning based classification of optical coherence tomography images with diabetic macular edema and dry age-related macular degeneration. Biomed. Opt. Express 8, 579–592 (2017)
-
(2017)
Biomed. Opt. Express
, vol.8
, pp. 579-592
-
-
Karri, S.P.K.1
Chakraborty, D.2
Chatterjee, J.3
-
18
-
-
85044634898
-
-
Preprint at
-
Apostolopoulos, S., Ciller, C., De Zanet, S. I., Wolf, S. & Sznitman, R. RetiNet: automatic AMD identification in OCT volumetric data. Preprint at http://arxiv.org/abs/1610.03628v1 (2016)
-
(2016)
Retinet: Automatic AMD Identification in OCT Volumetric Data
-
-
Apostolopoulos, S.1
Ciller, C.2
de Zanet, S.I.3
Wolf, S.4
Sznitman, R.5
-
19
-
-
84891629452
-
Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography
-
PID: 23993787
-
Farsiu, S. et al. Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography. Ophthalmology 121, 162–172 (2014)
-
(2014)
Ophthalmology
, vol.121
, pp. 162-172
-
-
Farsiu, S.1
-
20
-
-
84942367248
-
Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images
-
PID: 25360373
-
Srinivasan, P. P. et al. Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images. Biomed. Opt. Express 5, 3568–3577 (2014)
-
(2014)
Biomed. Opt. Express
, vol.5
, pp. 3568-3577
-
-
Srinivasan, P.P.1
-
21
-
-
85027881492
-
Deep learning is effective for classifying normal versus age-related macular degeneration OCT images
-
Lee, C. S., Baughman, D. M. & Lee, A. Y. Deep learning is effective for classifying normal versus age-related macular degeneration OCT images. Ophthalmol. Retin. 1, 322–327 (2017)
-
(2017)
Ophthalmol. Retin.
, vol.1
, pp. 322-327
-
-
Lee, C.S.1
Baughman, D.M.2
Lee, A.Y.3
-
22
-
-
85019034945
-
Automatic segmentation of nine retinal layer boundaries in OCT images of non-exudative AMD patients using deep learning and graph search
-
PID: 28663902
-
Fang, L. et al. Automatic segmentation of nine retinal layer boundaries in OCT images of non-exudative AMD patients using deep learning and graph search. Biomed. Opt. Express 8, 2732–2744 (2017)
-
(2017)
Biomed. Opt. Express
, vol.8
, pp. 2732-2744
-
-
Fang, L.1
-
23
-
-
85023600747
-
Deep-learning based, automated segmentation of macular edema in optical coherence tomography
-
PID: 28717579
-
Lee, C. S. et al. Deep-learning based, automated segmentation of macular edema in optical coherence tomography. Biomed. Opt. Express 8, 3440–3448 (2017)
-
(2017)
Biomed. Opt. Express
, vol.8
, pp. 3440-3448
-
-
Lee, C.S.1
-
25
-
-
85026815234
-
ReLayNet: retinal layer and fluid segmentation of macular optical coherence tomography using fully convolutional network
-
PID: 28856040
-
Roy, A. G. et al. ReLayNet: retinal layer and fluid segmentation of macular optical coherence tomography using fully convolutional network. Biomed. Opt. Express 8, 3627–3642 (2017)
-
(2017)
Biomed. Opt. Express
, vol.8
, pp. 3627-3642
-
-
Roy, A.G.1
-
26
-
-
84990235978
-
Can we open the black box of AI?
-
PID: 27708329
-
Castelvecchi, D. Can we open the black box of AI? Nature 538, 20–23 (2016)
-
(2016)
Nature
, vol.538
, pp. 20-23
-
-
Castelvecchi, D.1
-
27
-
-
85070485567
-
Machine learning to analyze the prognostic value of current imaging biomarkers in neovascular age-related macular degeneration
-
Schmidt-Erfurth, U. et al. Machine learning to analyze the prognostic value of current imaging biomarkers in neovascular age-related macular degeneration. Ophthalmol. Retin. 2, 24–30 (2018)
-
(2018)
Ophthalmol. Retin.
, vol.2
, pp. 24-30
-
-
Schmidt-Erfurth, U.1
-
28
-
-
85044656432
-
Fully automated detection and quantification of macular fluid in OCT using deep learning
-
PID: 29224926
-
Schlegl, T. et al. Fully automated detection and quantification of macular fluid in OCT using deep learning. Ophthalmology 125, 549–558 (2018)
-
(2018)
Ophthalmology
, vol.125
, pp. 549-558
-
-
Schlegl, T.1
-
29
-
-
79955035675
-
Predicting visual outcomes for macular disease using optical coherence tomography
-
PID: 23960916
-
Keane, P. A. & Sadda, S. R. Predicting visual outcomes for macular disease using optical coherence tomography. Saudi J. Ophthalmol. 25, 145–158 (2011)
-
(2011)
Saudi J. Ophthalmol.
, vol.25
, pp. 145-158
-
-
Keane, P.A.1
Sadda, S.R.2
-
30
-
-
84959483860
-
Anatomic clinical trial endpoints for nonexudative age-related macular degeneration
-
PID: 26952592
-
Schaal, K. B., Rosenfeld, P. J., Gregori, G., Yehoshua, Z. & Feuer, W. J. Anatomic clinical trial endpoints for nonexudative age-related macular degeneration. Ophthalmology 123, 1060–1079 (2016)
-
(2016)
Ophthalmology
, vol.123
, pp. 1060-1079
-
-
Schaal, K.B.1
Rosenfeld, P.J.2
Gregori, G.3
Yehoshua, Z.4
Feuer, W.J.5
-
31
-
-
84955388945
-
A paradigm shift in imaging biomarkers in neovascular age-related macular degeneration
-
PID: 26307399
-
Schmidt-Erfurth, U. & Waldstein, S. M. A paradigm shift in imaging biomarkers in neovascular age-related macular degeneration. Prog. Retin. Eye Res. 50, 1–24 (2016)
-
(2016)
Prog. Retin. Eye Res.
, vol.50
, pp. 1-24
-
-
Schmidt-Erfurth, U.1
Waldstein, S.M.2
-
32
-
-
85019864691
-
Decade-long profile of imaging biomarker use in ophthalmic clinical trials
-
PID: 28525561
-
Villani, E. et al. Decade-long profile of imaging biomarker use in ophthalmic clinical trials. Invest. Ophthalmol. Vis. Sci. 58, BIO76–BIO81 (2017)
-
(2017)
Invest. Ophthalmol. Vis. Sci.
, vol.58
, pp. BIO76-BIO81
-
-
Villani, E.1
-
33
-
-
85027721404
-
Human factor and usability testing of a binocular optical coherence tomography system
-
PID: 28824827
-
Chopra, R., Mulholland, P. J., Dubis, A. M., Anderson, R. S. & Keane, P. A. Human factor and usability testing of a binocular optical coherence tomography system. Transl. Vis. Sci. Technol. 6, 16 (2017)
-
(2017)
Transl. Vis. Sci. Technol.
, vol.6
, pp. 16
-
-
Chopra, R.1
Mulholland, P.J.2
Dubis, A.M.3
Anderson, R.S.4
Keane, P.A.5
-
34
-
-
84862520770
-
Fiji: an open-source platform for biological-image analysis
-
PID: 22743772
-
Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012)
-
(2012)
Nat. Methods
, vol.9
, pp. 676-682
-
-
Schindelin, J.1
-
35
-
-
84865157285
-
Evaluation of age-related macular degeneration with optical coherence tomography
-
PID: 22898648
-
Keane, P. A. et al. Evaluation of age-related macular degeneration with optical coherence tomography. Surv. Ophthalmol. 57, 389–414 (2012)
-
(2012)
Surv. Ophthalmol.
, vol.57
, pp. 389-414
-
-
Keane, P.A.1
-
36
-
-
84908120309
-
Comparison of optical coherence tomography assessments in the comparison of age-related macular degeneration treatments trials
-
PID: 24835760
-
Folgar, F. A. et al. Comparison of optical coherence tomography assessments in the comparison of age-related macular degeneration treatments trials. Ophthalmology 121, 1956–1965 (2014)
-
(2014)
Ophthalmology
, vol.121
, pp. 1956-1965
-
-
Folgar, F.A.1
-
37
-
-
84941874456
-
-
Elsevier Health Sciences, Oxford, UK
-
Duker, J. S., Waheed, N. K. & Goldman, D. Handbook of Retinal OCT: Optical Coherence Tomography E-Book (Elsevier Health Sciences, Oxford, UK; 2013)
-
(2013)
Handbook of Retinal OCT: Optical Coherence Tomography E-Book
-
-
Duker, J.S.1
Waheed, N.K.2
Goldman, D.3
-
38
-
-
84986296808
-
Rethinking the inception architecture for computer vision
-
Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J. & Wojna, Z. Rethinking the inception architecture for computer vision. Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. 2818–2826 (2016)
-
(2016)
Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit
, pp. 2818-2826
-
-
Szegedy, C.1
Vanhoucke, V.2
Ioffe, S.3
Shlens, J.4
Wojna, Z.5
-
41
-
-
85035343801
-
Densely connected convolutional networks
-
Huang, G., Liu, Z., Weinberger, K. Q. & van der Maaten, L. Densely connected convolutional networks. Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. 2261–2269 (2017)
-
(2017)
Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit
, pp. 2261-2269
-
-
Huang, G.1
Liu, Z.2
Weinberger, K.Q.3
van Der Maaten, L.4
-
43
-
-
85010976166
-
Automated analysis of retinal imaging using machine learning techniques for computer vision
-
PID: 27830057
-
De Fauw, J. et al. Automated analysis of retinal imaging using machine learning techniques for computer vision. F1000Res 5, 1573 (2016)
-
(2016)
F1000Res
, vol.5
, pp. 1573
-
-
De Fauw, J.1
|