Abstract

Non-perfusion area (NPA) is a quantitative biomarker useful for characterizing ischemia in diabetic retinopathy (DR). Projection-resolved optical coherence tomographic angiography (PR-OCTA) allows visualization of retinal capillaries and quantify NPA in individual plexuses. However, poor scan quality can make current NPA detection algorithms unreliable and inaccurate. In this work, we present a robust NPA detection algorithm using convolutional neural network (CNN). By merging information from OCT angiograms and OCT reflectance images, the CNN could exclude signal reduction and motion artifacts and detect the avascular features from local to global with the resolution preserved. Across a wide range of signal strength indices, and on both healthy and DR eyes, the algorithm achieved high accuracy and repeatability.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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Corrections

2 January 2020: A typographical correction was made to the author affiliations.


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References

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  1. Early Treatment Diabetic Retinopathy Study Research Group, “Fluorescein angiographic risk factors for progression of diabetic retinopathy: ETDRS report number 13,” Ophthalmology 98(5), 834–840 (1991).
    [Crossref]
  2. Diabetic Retinopathy Clinical Research Network, “Relationship between optical coherence tomography–measured central retinal thickness and visual acuity in diabetic macular edema,” Ophthalmology 114(3), 525–536 (2007).
    [Crossref]
  3. D. A. Sim, P. A. Keane, S. Fung, M. Karampelas, S. R. Sadda, M. Fruttiger, P. J. Patel, A. Tufail, and C. A. Egan, “Quantitative analysis of diabetic macular ischemia using optical coherence tomography,” Invest. Ophthalmol. Visual Sci. 55(1), 417–423 (2014).
    [Crossref]
  4. K. Sakata, H. Funatsu, S. Harino, H. Noma, and S. Hori, “Relationship between macular microcirculation and progression of diabetic macular edema,” Ophthalmology 113(8), 1385–1391 (2006).
    [Crossref]
  5. R. Klein, B. E. Klein, S. E. Moss, M. D. Davis, and D. L. DeMets, “The wisconsin epidemiologic study of diabetic retinopathy: Ii. prevalence and risk of diabetic retinopathy when age at diagnosis is less than 30 years,” Arch. Ophthalmol. 102(4), 520–526 (1984).
    [Crossref]
  6. A. Ishibazawa, T. Nagaoka, A. Takahashi, T. Omae, T. Tani, K. Sogawa, H. Yokota, and A. Yoshida, “Optical coherence tomography angiography in diabetic retinopathy: a prospective pilot study,” Am. J. Ophthalmol. 160(1), 35–44.e1 (2015).
    [Crossref]
  7. T. S. Hwang, A. M. Hagag, J. Wang, M. Zhang, A. Smith, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion areas in 3 vascular plexuses with optical coherence tomography angiography in eyes of patients with diabetes,” JAMA Ophthalmol. 136(8), 929–936 (2018).
    [Crossref]
  8. T. S. Hwang, Y. Jia, S. S. Gao, S. T. Bailey, A. K. Lauer, C. J. Flaxel, D. J. Wilson, and D. Huang, “Optical coherence tomography angiography features of diabetic retinopathy,” Retina 35(11), 2371–2376 (2015).
    [Crossref]
  9. T. S. Hwang, M. Zhang, K. Bhavsar, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. K. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Visualization of 3 distinct retinal plexuses by projection-resolved optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
    [Crossref]
  10. D. Y. Lin, M. S. Blumenkranz, R. J. Brothers, D. M. Grosvenor, and T. D. D. S. Group, “The sensitivity and specificity of single-field nonmydriatic monochromatic digital fundus photography with remote image interpretation for diabetic retinopathy screening: a comparison with ophthalmoscopy and standardized mydriatic color photography,” Am. J. Ophthalmol. 134(2), 204–213 (2002).
    [Crossref]
  11. M. M. Wessel, N. Nair, G. D. Aaker, J. R. Ehrlich, D. J. D’Amico, and S. Kiss, “Peripheral retinal ischaemia, as evaluated by ultra-widefield fluorescein angiography, is associated with diabetic macular oedema,” Br. J. Ophthalmol. 96(5), 694–698 (2012).
    [Crossref]
  12. C. Shen, S. Yan, M. Du, H. Zhao, L. Shao, and Y. Hu, “Assessment of capillary dropout in the superficial retinal capillary plexus by optical coherence tomography angiography in the early stage of diabetic retinopathy,” BMC Ophthalmol. 18(1), 113 (2018).
    [Crossref]
  13. Y. Jia, S. T. Bailey, T. S. Hwang, S. M. McClintic, S. S. Gao, M. E. Pennesi, C. J. Flaxel, A. K. Lauer, D. J. Wilson, J. Hornegger, J. G. Fujimoto, and D. Huang, “Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye,” Proc. Natl. Acad. Sci. 112(18), E2395–E2402 (2015).
    [Crossref]
  14. T. S. Hwang, S. S. Gao, L. Liu, A. K. Lauer, S. T. Bailey, C. J. Flaxel, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of capillary nonperfusion using optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(4), 367–373 (2016).
    [Crossref]
  15. J. Wang, M. Zhang, T. S. Hwang, S. T. Bailey, D. Huang, D. J. Wilson, and Y. Jia, “Reflectance-based projection-resolved optical coherence tomography angiography,” Biomed. Opt. Express 8(3), 1536–1548 (2017).
    [Crossref]
  16. M. Zhang, T. S. Hwang, J. P. Campbell, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Projection-resolved optical coherence tomographic angiography,” Biomed. Opt. Express 7(3), 816–828 (2016).
    [Crossref]
  17. R. C. Patel, J. Wang, T. S. Hwang, M. Zhang, S. S. Gao, M. E. Pennesi, S. T. Bailey, B. J. Lujan, X. Wang, D. J. Wilson, D. Huang, and Y. Jia, “Plexus-specific detection of retinal vascular pathologic conditions with projection-resolved oct angiography,” Ophthalmol. Retin. 2(8), 816–826 (2018).
    [Crossref]
  18. J. J. Park, C. S. Chung, and A. A. Fawzi, “Visualizing structure and vascular interactions: macular nonperfusion in three capillary plexuses,” Ophthalmic Surgery, Lasers Imaging Retin. 49(11), e182–e190 (2018).
    [Crossref]
  19. M. Zhang, T. S. Hwang, C. Dongye, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion in three retinal plexuses using projection-resolved optical coherence tomography angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 57(13), 5101–5106 (2016).
    [Crossref]
  20. Y. Guo, A. Camino, J. Wang, D. Huang, T. S. Hwang, and Y. Jia, “Mednet, a neural network for automated detection of avascular area in oct angiography,” Biomed. Opt. Express 9(11), 5147–5158 (2018).
    [Crossref]
  21. Y. Guo, T. T. Hormel, H. Xiong, B. Wang, A. Camino, J. Wang, D. Huang, T. S. Hwang, and Y. Jia, “Development and validation of a deep learning algorithm for distinguishing the nonperfusion area from signal reduction artifacts on oct angiography,” Biomed. Opt. Express 10(7), 3257–3268 (2019).
    [Crossref]
  22. Y. Jia, O. Tan, J. Tokayer, B. Potsaid, Y. Wang, J. J. Liu, M. F. Kraus, H. Subhash, J. G. Fujimoto, J. Hornegger, and D. Huang, “Split-spectrum amplitude-decorrelation angiography with optical coherence tomography,” Opt. Express 20(4), 4710–4725 (2012).
    [Crossref]
  23. M. F. Kraus, B. Potsaid, M. A. Mayer, R. Bock, B. Baumann, J. J. Liu, J. Hornegger, and J. G. Fujimoto, “Motion correction in optical coherence tomography volumes on a per a-scan basis using orthogonal scan patterns,” Biomed. Opt. Express 3(6), 1182–1199 (2012).
    [Crossref]
  24. M. Zhang, J. Wang, A. D. Pechauer, T. S. Hwang, S. S. Gao, L. Liu, L. Liu, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Advanced image processing for optical coherence tomographic angiography of macular diseases,” Biomed. Opt. Express 6(12), 4661–4675 (2015).
    [Crossref]
  25. Y. Guo, A. Camino, M. Zhang, J. Wang, D. Huang, T. Hwang, and Y. Jia, “Automated segmentation of retinal layer boundaries and capillary plexuses in wide-field optical coherence tomographic angiography,” Biomed. Opt. Express 9(9), 4429–4442 (2018).
    [Crossref]
  26. J. Campbell, M. Zhang, T. Hwang, S. Bailey, D. Wilson, Y. Jia, and D. Huang, “Detailed vascular anatomy of the human retina by projection-resolved optical coherence tomography angiography,” Sci. Rep. 7(1), 42201 (2017).
    [Crossref]
  27. J. J. Yu, A. Camino, L. Liu, X. Zhang, J. Wang, S. S. Gao, Y. Jia, and D. Huang, “Signal strength reduction effects in oct angiography,” Ophthalmol. Retin. 3(10), 835–842 (2019).
    [Crossref]
  28. S. A. Agemy, N. K. Scripsema, C. M. Shah, T. Chui, P. M. Garcia, J. G. Lee, R. C. Gentile, Y.-S. Hsiao, Q. Zhou, T. Ko, and R. Richard B., “Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients,” Retina 35(11), 2353–2363 (2015).
    [Crossref]
  29. P. L. Nesper, P. K. Roberts, A. C. Onishi, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Quantifying microvascular abnormalities with increasing severity of diabetic retinopathy using optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 58(6), BIO307 (2017).
    [Crossref]
  30. A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).
  31. J. Schottenhamml, E. M. Moult, S. Ploner, B. Lee, E. A. Novais, E. Cole, S. Dang, C. D. Lu, L. Husvogt, N. K. Waheed, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “An automatic intercapillary area based algorithm for quantifying diabetes related capillary dropout using oct angiography,” Retina 36, S93–S101 (2016).
    [Crossref]
  32. A. C. Onishi, P. L. Nesper, P. K. Roberts, G. A. Moharram, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Importance of considering the middle capillary plexus on oct angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 59(5), 2167–2176 (2018).
    [Crossref]
  33. L. Liu, S. S. Gao, S. T. Bailey, D. Huang, D. Li, and Y. Jia, “Automated choroidal neovascularization detection algorithm for optical coherence tomography angiography,” Biomed. Opt. Express 6(9), 3564–3576 (2015).
    [Crossref]
  34. K. Morino, T. Murakami, Y. Dodo, S. Yasukura, T. Yoshitake, M. Fujimoto, and A. Tsujikawa, “Characteristics of diabetic capillary nonperfusion in macular and extramacular white spots on optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 60(5), 1595–1603 (2019).
    [Crossref]

2019 (3)

Y. Guo, T. T. Hormel, H. Xiong, B. Wang, A. Camino, J. Wang, D. Huang, T. S. Hwang, and Y. Jia, “Development and validation of a deep learning algorithm for distinguishing the nonperfusion area from signal reduction artifacts on oct angiography,” Biomed. Opt. Express 10(7), 3257–3268 (2019).
[Crossref]

J. J. Yu, A. Camino, L. Liu, X. Zhang, J. Wang, S. S. Gao, Y. Jia, and D. Huang, “Signal strength reduction effects in oct angiography,” Ophthalmol. Retin. 3(10), 835–842 (2019).
[Crossref]

K. Morino, T. Murakami, Y. Dodo, S. Yasukura, T. Yoshitake, M. Fujimoto, and A. Tsujikawa, “Characteristics of diabetic capillary nonperfusion in macular and extramacular white spots on optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 60(5), 1595–1603 (2019).
[Crossref]

2018 (7)

A. C. Onishi, P. L. Nesper, P. K. Roberts, G. A. Moharram, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Importance of considering the middle capillary plexus on oct angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 59(5), 2167–2176 (2018).
[Crossref]

Y. Guo, A. Camino, M. Zhang, J. Wang, D. Huang, T. Hwang, and Y. Jia, “Automated segmentation of retinal layer boundaries and capillary plexuses in wide-field optical coherence tomographic angiography,” Biomed. Opt. Express 9(9), 4429–4442 (2018).
[Crossref]

Y. Guo, A. Camino, J. Wang, D. Huang, T. S. Hwang, and Y. Jia, “Mednet, a neural network for automated detection of avascular area in oct angiography,” Biomed. Opt. Express 9(11), 5147–5158 (2018).
[Crossref]

T. S. Hwang, A. M. Hagag, J. Wang, M. Zhang, A. Smith, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion areas in 3 vascular plexuses with optical coherence tomography angiography in eyes of patients with diabetes,” JAMA Ophthalmol. 136(8), 929–936 (2018).
[Crossref]

C. Shen, S. Yan, M. Du, H. Zhao, L. Shao, and Y. Hu, “Assessment of capillary dropout in the superficial retinal capillary plexus by optical coherence tomography angiography in the early stage of diabetic retinopathy,” BMC Ophthalmol. 18(1), 113 (2018).
[Crossref]

R. C. Patel, J. Wang, T. S. Hwang, M. Zhang, S. S. Gao, M. E. Pennesi, S. T. Bailey, B. J. Lujan, X. Wang, D. J. Wilson, D. Huang, and Y. Jia, “Plexus-specific detection of retinal vascular pathologic conditions with projection-resolved oct angiography,” Ophthalmol. Retin. 2(8), 816–826 (2018).
[Crossref]

J. J. Park, C. S. Chung, and A. A. Fawzi, “Visualizing structure and vascular interactions: macular nonperfusion in three capillary plexuses,” Ophthalmic Surgery, Lasers Imaging Retin. 49(11), e182–e190 (2018).
[Crossref]

2017 (3)

J. Wang, M. Zhang, T. S. Hwang, S. T. Bailey, D. Huang, D. J. Wilson, and Y. Jia, “Reflectance-based projection-resolved optical coherence tomography angiography,” Biomed. Opt. Express 8(3), 1536–1548 (2017).
[Crossref]

J. Campbell, M. Zhang, T. Hwang, S. Bailey, D. Wilson, Y. Jia, and D. Huang, “Detailed vascular anatomy of the human retina by projection-resolved optical coherence tomography angiography,” Sci. Rep. 7(1), 42201 (2017).
[Crossref]

P. L. Nesper, P. K. Roberts, A. C. Onishi, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Quantifying microvascular abnormalities with increasing severity of diabetic retinopathy using optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 58(6), BIO307 (2017).
[Crossref]

2016 (5)

J. Schottenhamml, E. M. Moult, S. Ploner, B. Lee, E. A. Novais, E. Cole, S. Dang, C. D. Lu, L. Husvogt, N. K. Waheed, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “An automatic intercapillary area based algorithm for quantifying diabetes related capillary dropout using oct angiography,” Retina 36, S93–S101 (2016).
[Crossref]

T. S. Hwang, S. S. Gao, L. Liu, A. K. Lauer, S. T. Bailey, C. J. Flaxel, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of capillary nonperfusion using optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(4), 367–373 (2016).
[Crossref]

M. Zhang, T. S. Hwang, J. P. Campbell, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Projection-resolved optical coherence tomographic angiography,” Biomed. Opt. Express 7(3), 816–828 (2016).
[Crossref]

M. Zhang, T. S. Hwang, C. Dongye, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion in three retinal plexuses using projection-resolved optical coherence tomography angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 57(13), 5101–5106 (2016).
[Crossref]

T. S. Hwang, M. Zhang, K. Bhavsar, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. K. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Visualization of 3 distinct retinal plexuses by projection-resolved optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
[Crossref]

2015 (6)

T. S. Hwang, Y. Jia, S. S. Gao, S. T. Bailey, A. K. Lauer, C. J. Flaxel, D. J. Wilson, and D. Huang, “Optical coherence tomography angiography features of diabetic retinopathy,” Retina 35(11), 2371–2376 (2015).
[Crossref]

Y. Jia, S. T. Bailey, T. S. Hwang, S. M. McClintic, S. S. Gao, M. E. Pennesi, C. J. Flaxel, A. K. Lauer, D. J. Wilson, J. Hornegger, J. G. Fujimoto, and D. Huang, “Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye,” Proc. Natl. Acad. Sci. 112(18), E2395–E2402 (2015).
[Crossref]

A. Ishibazawa, T. Nagaoka, A. Takahashi, T. Omae, T. Tani, K. Sogawa, H. Yokota, and A. Yoshida, “Optical coherence tomography angiography in diabetic retinopathy: a prospective pilot study,” Am. J. Ophthalmol. 160(1), 35–44.e1 (2015).
[Crossref]

S. A. Agemy, N. K. Scripsema, C. M. Shah, T. Chui, P. M. Garcia, J. G. Lee, R. C. Gentile, Y.-S. Hsiao, Q. Zhou, T. Ko, and R. Richard B., “Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients,” Retina 35(11), 2353–2363 (2015).
[Crossref]

L. Liu, S. S. Gao, S. T. Bailey, D. Huang, D. Li, and Y. Jia, “Automated choroidal neovascularization detection algorithm for optical coherence tomography angiography,” Biomed. Opt. Express 6(9), 3564–3576 (2015).
[Crossref]

M. Zhang, J. Wang, A. D. Pechauer, T. S. Hwang, S. S. Gao, L. Liu, L. Liu, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Advanced image processing for optical coherence tomographic angiography of macular diseases,” Biomed. Opt. Express 6(12), 4661–4675 (2015).
[Crossref]

2014 (1)

D. A. Sim, P. A. Keane, S. Fung, M. Karampelas, S. R. Sadda, M. Fruttiger, P. J. Patel, A. Tufail, and C. A. Egan, “Quantitative analysis of diabetic macular ischemia using optical coherence tomography,” Invest. Ophthalmol. Visual Sci. 55(1), 417–423 (2014).
[Crossref]

2012 (3)

2007 (1)

Diabetic Retinopathy Clinical Research Network, “Relationship between optical coherence tomography–measured central retinal thickness and visual acuity in diabetic macular edema,” Ophthalmology 114(3), 525–536 (2007).
[Crossref]

2006 (1)

K. Sakata, H. Funatsu, S. Harino, H. Noma, and S. Hori, “Relationship between macular microcirculation and progression of diabetic macular edema,” Ophthalmology 113(8), 1385–1391 (2006).
[Crossref]

2002 (1)

D. Y. Lin, M. S. Blumenkranz, R. J. Brothers, D. M. Grosvenor, and T. D. D. S. Group, “The sensitivity and specificity of single-field nonmydriatic monochromatic digital fundus photography with remote image interpretation for diabetic retinopathy screening: a comparison with ophthalmoscopy and standardized mydriatic color photography,” Am. J. Ophthalmol. 134(2), 204–213 (2002).
[Crossref]

1991 (1)

Early Treatment Diabetic Retinopathy Study Research Group, “Fluorescein angiographic risk factors for progression of diabetic retinopathy: ETDRS report number 13,” Ophthalmology 98(5), 834–840 (1991).
[Crossref]

1984 (1)

R. Klein, B. E. Klein, S. E. Moss, M. D. Davis, and D. L. DeMets, “The wisconsin epidemiologic study of diabetic retinopathy: Ii. prevalence and risk of diabetic retinopathy when age at diagnosis is less than 30 years,” Arch. Ophthalmol. 102(4), 520–526 (1984).
[Crossref]

Aaker, G. D.

M. M. Wessel, N. Nair, G. D. Aaker, J. R. Ehrlich, D. J. D’Amico, and S. Kiss, “Peripheral retinal ischaemia, as evaluated by ultra-widefield fluorescein angiography, is associated with diabetic macular oedema,” Br. J. Ophthalmol. 96(5), 694–698 (2012).
[Crossref]

Agemy, S. A.

S. A. Agemy, N. K. Scripsema, C. M. Shah, T. Chui, P. M. Garcia, J. G. Lee, R. C. Gentile, Y.-S. Hsiao, Q. Zhou, T. Ko, and R. Richard B., “Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients,” Retina 35(11), 2353–2363 (2015).
[Crossref]

Alibhai, A. Y.

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

Arya, M.

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

Bailey, S.

J. Campbell, M. Zhang, T. Hwang, S. Bailey, D. Wilson, Y. Jia, and D. Huang, “Detailed vascular anatomy of the human retina by projection-resolved optical coherence tomography angiography,” Sci. Rep. 7(1), 42201 (2017).
[Crossref]

Bailey, S. T.

R. C. Patel, J. Wang, T. S. Hwang, M. Zhang, S. S. Gao, M. E. Pennesi, S. T. Bailey, B. J. Lujan, X. Wang, D. J. Wilson, D. Huang, and Y. Jia, “Plexus-specific detection of retinal vascular pathologic conditions with projection-resolved oct angiography,” Ophthalmol. Retin. 2(8), 816–826 (2018).
[Crossref]

J. Wang, M. Zhang, T. S. Hwang, S. T. Bailey, D. Huang, D. J. Wilson, and Y. Jia, “Reflectance-based projection-resolved optical coherence tomography angiography,” Biomed. Opt. Express 8(3), 1536–1548 (2017).
[Crossref]

T. S. Hwang, S. S. Gao, L. Liu, A. K. Lauer, S. T. Bailey, C. J. Flaxel, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of capillary nonperfusion using optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(4), 367–373 (2016).
[Crossref]

T. S. Hwang, M. Zhang, K. Bhavsar, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. K. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Visualization of 3 distinct retinal plexuses by projection-resolved optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
[Crossref]

M. Zhang, T. S. Hwang, J. P. Campbell, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Projection-resolved optical coherence tomographic angiography,” Biomed. Opt. Express 7(3), 816–828 (2016).
[Crossref]

T. S. Hwang, Y. Jia, S. S. Gao, S. T. Bailey, A. K. Lauer, C. J. Flaxel, D. J. Wilson, and D. Huang, “Optical coherence tomography angiography features of diabetic retinopathy,” Retina 35(11), 2371–2376 (2015).
[Crossref]

Y. Jia, S. T. Bailey, T. S. Hwang, S. M. McClintic, S. S. Gao, M. E. Pennesi, C. J. Flaxel, A. K. Lauer, D. J. Wilson, J. Hornegger, J. G. Fujimoto, and D. Huang, “Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye,” Proc. Natl. Acad. Sci. 112(18), E2395–E2402 (2015).
[Crossref]

M. Zhang, J. Wang, A. D. Pechauer, T. S. Hwang, S. S. Gao, L. Liu, L. Liu, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Advanced image processing for optical coherence tomographic angiography of macular diseases,” Biomed. Opt. Express 6(12), 4661–4675 (2015).
[Crossref]

L. Liu, S. S. Gao, S. T. Bailey, D. Huang, D. Li, and Y. Jia, “Automated choroidal neovascularization detection algorithm for optical coherence tomography angiography,” Biomed. Opt. Express 6(9), 3564–3576 (2015).
[Crossref]

Baumal, C. R.

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

Baumann, B.

Bhavsar, K.

T. S. Hwang, M. Zhang, K. Bhavsar, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. K. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Visualization of 3 distinct retinal plexuses by projection-resolved optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
[Crossref]

Blumenkranz, M. S.

D. Y. Lin, M. S. Blumenkranz, R. J. Brothers, D. M. Grosvenor, and T. D. D. S. Group, “The sensitivity and specificity of single-field nonmydriatic monochromatic digital fundus photography with remote image interpretation for diabetic retinopathy screening: a comparison with ophthalmoscopy and standardized mydriatic color photography,” Am. J. Ophthalmol. 134(2), 204–213 (2002).
[Crossref]

Bock, R.

Brothers, R. J.

D. Y. Lin, M. S. Blumenkranz, R. J. Brothers, D. M. Grosvenor, and T. D. D. S. Group, “The sensitivity and specificity of single-field nonmydriatic monochromatic digital fundus photography with remote image interpretation for diabetic retinopathy screening: a comparison with ophthalmoscopy and standardized mydriatic color photography,” Am. J. Ophthalmol. 134(2), 204–213 (2002).
[Crossref]

Camino, A.

Campbell, J.

J. Campbell, M. Zhang, T. Hwang, S. Bailey, D. Wilson, Y. Jia, and D. Huang, “Detailed vascular anatomy of the human retina by projection-resolved optical coherence tomography angiography,” Sci. Rep. 7(1), 42201 (2017).
[Crossref]

Campbell, J. P.

T. S. Hwang, M. Zhang, K. Bhavsar, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. K. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Visualization of 3 distinct retinal plexuses by projection-resolved optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
[Crossref]

M. Zhang, T. S. Hwang, J. P. Campbell, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Projection-resolved optical coherence tomographic angiography,” Biomed. Opt. Express 7(3), 816–828 (2016).
[Crossref]

Carrasco-Zevallos, O.

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

Chai, H.

A. C. Onishi, P. L. Nesper, P. K. Roberts, G. A. Moharram, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Importance of considering the middle capillary plexus on oct angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 59(5), 2167–2176 (2018).
[Crossref]

P. L. Nesper, P. K. Roberts, A. C. Onishi, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Quantifying microvascular abnormalities with increasing severity of diabetic retinopathy using optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 58(6), BIO307 (2017).
[Crossref]

Chen, S.

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

Chui, T.

S. A. Agemy, N. K. Scripsema, C. M. Shah, T. Chui, P. M. Garcia, J. G. Lee, R. C. Gentile, Y.-S. Hsiao, Q. Zhou, T. Ko, and R. Richard B., “Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients,” Retina 35(11), 2353–2363 (2015).
[Crossref]

Chung, C. S.

J. J. Park, C. S. Chung, and A. A. Fawzi, “Visualizing structure and vascular interactions: macular nonperfusion in three capillary plexuses,” Ophthalmic Surgery, Lasers Imaging Retin. 49(11), e182–e190 (2018).
[Crossref]

Cole, E.

J. Schottenhamml, E. M. Moult, S. Ploner, B. Lee, E. A. Novais, E. Cole, S. Dang, C. D. Lu, L. Husvogt, N. K. Waheed, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “An automatic intercapillary area based algorithm for quantifying diabetes related capillary dropout using oct angiography,” Retina 36, S93–S101 (2016).
[Crossref]

D’Amico, D. J.

M. M. Wessel, N. Nair, G. D. Aaker, J. R. Ehrlich, D. J. D’Amico, and S. Kiss, “Peripheral retinal ischaemia, as evaluated by ultra-widefield fluorescein angiography, is associated with diabetic macular oedema,” Br. J. Ophthalmol. 96(5), 694–698 (2012).
[Crossref]

Dang, S.

J. Schottenhamml, E. M. Moult, S. Ploner, B. Lee, E. A. Novais, E. Cole, S. Dang, C. D. Lu, L. Husvogt, N. K. Waheed, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “An automatic intercapillary area based algorithm for quantifying diabetes related capillary dropout using oct angiography,” Retina 36, S93–S101 (2016).
[Crossref]

Davis, M. D.

R. Klein, B. E. Klein, S. E. Moss, M. D. Davis, and D. L. DeMets, “The wisconsin epidemiologic study of diabetic retinopathy: Ii. prevalence and risk of diabetic retinopathy when age at diagnosis is less than 30 years,” Arch. Ophthalmol. 102(4), 520–526 (1984).
[Crossref]

de Freitas, A. Z.

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

De Pretto, L. R.

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

DeMets, D. L.

R. Klein, B. E. Klein, S. E. Moss, M. D. Davis, and D. L. DeMets, “The wisconsin epidemiologic study of diabetic retinopathy: Ii. prevalence and risk of diabetic retinopathy when age at diagnosis is less than 30 years,” Arch. Ophthalmol. 102(4), 520–526 (1984).
[Crossref]

Dodo, Y.

K. Morino, T. Murakami, Y. Dodo, S. Yasukura, T. Yoshitake, M. Fujimoto, and A. Tsujikawa, “Characteristics of diabetic capillary nonperfusion in macular and extramacular white spots on optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 60(5), 1595–1603 (2019).
[Crossref]

Dongye, C.

M. Zhang, T. S. Hwang, C. Dongye, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion in three retinal plexuses using projection-resolved optical coherence tomography angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 57(13), 5101–5106 (2016).
[Crossref]

Du, M.

C. Shen, S. Yan, M. Du, H. Zhao, L. Shao, and Y. Hu, “Assessment of capillary dropout in the superficial retinal capillary plexus by optical coherence tomography angiography in the early stage of diabetic retinopathy,” BMC Ophthalmol. 18(1), 113 (2018).
[Crossref]

Duker, J. S.

J. Schottenhamml, E. M. Moult, S. Ploner, B. Lee, E. A. Novais, E. Cole, S. Dang, C. D. Lu, L. Husvogt, N. K. Waheed, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “An automatic intercapillary area based algorithm for quantifying diabetes related capillary dropout using oct angiography,” Retina 36, S93–S101 (2016).
[Crossref]

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

Egan, C. A.

D. A. Sim, P. A. Keane, S. Fung, M. Karampelas, S. R. Sadda, M. Fruttiger, P. J. Patel, A. Tufail, and C. A. Egan, “Quantitative analysis of diabetic macular ischemia using optical coherence tomography,” Invest. Ophthalmol. Visual Sci. 55(1), 417–423 (2014).
[Crossref]

Ehrlich, J. R.

M. M. Wessel, N. Nair, G. D. Aaker, J. R. Ehrlich, D. J. D’Amico, and S. Kiss, “Peripheral retinal ischaemia, as evaluated by ultra-widefield fluorescein angiography, is associated with diabetic macular oedema,” Br. J. Ophthalmol. 96(5), 694–698 (2012).
[Crossref]

Fawzi, A. A.

J. J. Park, C. S. Chung, and A. A. Fawzi, “Visualizing structure and vascular interactions: macular nonperfusion in three capillary plexuses,” Ophthalmic Surgery, Lasers Imaging Retin. 49(11), e182–e190 (2018).
[Crossref]

A. C. Onishi, P. L. Nesper, P. K. Roberts, G. A. Moharram, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Importance of considering the middle capillary plexus on oct angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 59(5), 2167–2176 (2018).
[Crossref]

P. L. Nesper, P. K. Roberts, A. C. Onishi, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Quantifying microvascular abnormalities with increasing severity of diabetic retinopathy using optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 58(6), BIO307 (2017).
[Crossref]

Flaxel, C. J.

T. S. Hwang, S. S. Gao, L. Liu, A. K. Lauer, S. T. Bailey, C. J. Flaxel, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of capillary nonperfusion using optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(4), 367–373 (2016).
[Crossref]

T. S. Hwang, M. Zhang, K. Bhavsar, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. K. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Visualization of 3 distinct retinal plexuses by projection-resolved optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
[Crossref]

T. S. Hwang, Y. Jia, S. S. Gao, S. T. Bailey, A. K. Lauer, C. J. Flaxel, D. J. Wilson, and D. Huang, “Optical coherence tomography angiography features of diabetic retinopathy,” Retina 35(11), 2371–2376 (2015).
[Crossref]

Y. Jia, S. T. Bailey, T. S. Hwang, S. M. McClintic, S. S. Gao, M. E. Pennesi, C. J. Flaxel, A. K. Lauer, D. J. Wilson, J. Hornegger, J. G. Fujimoto, and D. Huang, “Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye,” Proc. Natl. Acad. Sci. 112(18), E2395–E2402 (2015).
[Crossref]

Fruttiger, M.

D. A. Sim, P. A. Keane, S. Fung, M. Karampelas, S. R. Sadda, M. Fruttiger, P. J. Patel, A. Tufail, and C. A. Egan, “Quantitative analysis of diabetic macular ischemia using optical coherence tomography,” Invest. Ophthalmol. Visual Sci. 55(1), 417–423 (2014).
[Crossref]

Fujimoto, J. G.

J. Schottenhamml, E. M. Moult, S. Ploner, B. Lee, E. A. Novais, E. Cole, S. Dang, C. D. Lu, L. Husvogt, N. K. Waheed, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “An automatic intercapillary area based algorithm for quantifying diabetes related capillary dropout using oct angiography,” Retina 36, S93–S101 (2016).
[Crossref]

Y. Jia, S. T. Bailey, T. S. Hwang, S. M. McClintic, S. S. Gao, M. E. Pennesi, C. J. Flaxel, A. K. Lauer, D. J. Wilson, J. Hornegger, J. G. Fujimoto, and D. Huang, “Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye,” Proc. Natl. Acad. Sci. 112(18), E2395–E2402 (2015).
[Crossref]

Y. Jia, O. Tan, J. Tokayer, B. Potsaid, Y. Wang, J. J. Liu, M. F. Kraus, H. Subhash, J. G. Fujimoto, J. Hornegger, and D. Huang, “Split-spectrum amplitude-decorrelation angiography with optical coherence tomography,” Opt. Express 20(4), 4710–4725 (2012).
[Crossref]

M. F. Kraus, B. Potsaid, M. A. Mayer, R. Bock, B. Baumann, J. J. Liu, J. Hornegger, and J. G. Fujimoto, “Motion correction in optical coherence tomography volumes on a per a-scan basis using orthogonal scan patterns,” Biomed. Opt. Express 3(6), 1182–1199 (2012).
[Crossref]

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

Fujimoto, M.

K. Morino, T. Murakami, Y. Dodo, S. Yasukura, T. Yoshitake, M. Fujimoto, and A. Tsujikawa, “Characteristics of diabetic capillary nonperfusion in macular and extramacular white spots on optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 60(5), 1595–1603 (2019).
[Crossref]

Funatsu, H.

K. Sakata, H. Funatsu, S. Harino, H. Noma, and S. Hori, “Relationship between macular microcirculation and progression of diabetic macular edema,” Ophthalmology 113(8), 1385–1391 (2006).
[Crossref]

Fung, S.

D. A. Sim, P. A. Keane, S. Fung, M. Karampelas, S. R. Sadda, M. Fruttiger, P. J. Patel, A. Tufail, and C. A. Egan, “Quantitative analysis of diabetic macular ischemia using optical coherence tomography,” Invest. Ophthalmol. Visual Sci. 55(1), 417–423 (2014).
[Crossref]

Gao, S. S.

J. J. Yu, A. Camino, L. Liu, X. Zhang, J. Wang, S. S. Gao, Y. Jia, and D. Huang, “Signal strength reduction effects in oct angiography,” Ophthalmol. Retin. 3(10), 835–842 (2019).
[Crossref]

R. C. Patel, J. Wang, T. S. Hwang, M. Zhang, S. S. Gao, M. E. Pennesi, S. T. Bailey, B. J. Lujan, X. Wang, D. J. Wilson, D. Huang, and Y. Jia, “Plexus-specific detection of retinal vascular pathologic conditions with projection-resolved oct angiography,” Ophthalmol. Retin. 2(8), 816–826 (2018).
[Crossref]

T. S. Hwang, S. S. Gao, L. Liu, A. K. Lauer, S. T. Bailey, C. J. Flaxel, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of capillary nonperfusion using optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(4), 367–373 (2016).
[Crossref]

Y. Jia, S. T. Bailey, T. S. Hwang, S. M. McClintic, S. S. Gao, M. E. Pennesi, C. J. Flaxel, A. K. Lauer, D. J. Wilson, J. Hornegger, J. G. Fujimoto, and D. Huang, “Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye,” Proc. Natl. Acad. Sci. 112(18), E2395–E2402 (2015).
[Crossref]

T. S. Hwang, Y. Jia, S. S. Gao, S. T. Bailey, A. K. Lauer, C. J. Flaxel, D. J. Wilson, and D. Huang, “Optical coherence tomography angiography features of diabetic retinopathy,” Retina 35(11), 2371–2376 (2015).
[Crossref]

M. Zhang, J. Wang, A. D. Pechauer, T. S. Hwang, S. S. Gao, L. Liu, L. Liu, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Advanced image processing for optical coherence tomographic angiography of macular diseases,” Biomed. Opt. Express 6(12), 4661–4675 (2015).
[Crossref]

L. Liu, S. S. Gao, S. T. Bailey, D. Huang, D. Li, and Y. Jia, “Automated choroidal neovascularization detection algorithm for optical coherence tomography angiography,” Biomed. Opt. Express 6(9), 3564–3576 (2015).
[Crossref]

Garcia, P. M.

S. A. Agemy, N. K. Scripsema, C. M. Shah, T. Chui, P. M. Garcia, J. G. Lee, R. C. Gentile, Y.-S. Hsiao, Q. Zhou, T. Ko, and R. Richard B., “Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients,” Retina 35(11), 2353–2363 (2015).
[Crossref]

Gentile, R. C.

S. A. Agemy, N. K. Scripsema, C. M. Shah, T. Chui, P. M. Garcia, J. G. Lee, R. C. Gentile, Y.-S. Hsiao, Q. Zhou, T. Ko, and R. Richard B., “Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients,” Retina 35(11), 2353–2363 (2015).
[Crossref]

Grosvenor, D. M.

D. Y. Lin, M. S. Blumenkranz, R. J. Brothers, D. M. Grosvenor, and T. D. D. S. Group, “The sensitivity and specificity of single-field nonmydriatic monochromatic digital fundus photography with remote image interpretation for diabetic retinopathy screening: a comparison with ophthalmoscopy and standardized mydriatic color photography,” Am. J. Ophthalmol. 134(2), 204–213 (2002).
[Crossref]

Guo, Y.

Hagag, A. M.

T. S. Hwang, A. M. Hagag, J. Wang, M. Zhang, A. Smith, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion areas in 3 vascular plexuses with optical coherence tomography angiography in eyes of patients with diabetes,” JAMA Ophthalmol. 136(8), 929–936 (2018).
[Crossref]

Harino, S.

K. Sakata, H. Funatsu, S. Harino, H. Noma, and S. Hori, “Relationship between macular microcirculation and progression of diabetic macular edema,” Ophthalmology 113(8), 1385–1391 (2006).
[Crossref]

Hori, S.

K. Sakata, H. Funatsu, S. Harino, H. Noma, and S. Hori, “Relationship between macular microcirculation and progression of diabetic macular edema,” Ophthalmology 113(8), 1385–1391 (2006).
[Crossref]

Hormel, T. T.

Hornegger, J.

J. Schottenhamml, E. M. Moult, S. Ploner, B. Lee, E. A. Novais, E. Cole, S. Dang, C. D. Lu, L. Husvogt, N. K. Waheed, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “An automatic intercapillary area based algorithm for quantifying diabetes related capillary dropout using oct angiography,” Retina 36, S93–S101 (2016).
[Crossref]

Y. Jia, S. T. Bailey, T. S. Hwang, S. M. McClintic, S. S. Gao, M. E. Pennesi, C. J. Flaxel, A. K. Lauer, D. J. Wilson, J. Hornegger, J. G. Fujimoto, and D. Huang, “Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye,” Proc. Natl. Acad. Sci. 112(18), E2395–E2402 (2015).
[Crossref]

Y. Jia, O. Tan, J. Tokayer, B. Potsaid, Y. Wang, J. J. Liu, M. F. Kraus, H. Subhash, J. G. Fujimoto, J. Hornegger, and D. Huang, “Split-spectrum amplitude-decorrelation angiography with optical coherence tomography,” Opt. Express 20(4), 4710–4725 (2012).
[Crossref]

M. F. Kraus, B. Potsaid, M. A. Mayer, R. Bock, B. Baumann, J. J. Liu, J. Hornegger, and J. G. Fujimoto, “Motion correction in optical coherence tomography volumes on a per a-scan basis using orthogonal scan patterns,” Biomed. Opt. Express 3(6), 1182–1199 (2012).
[Crossref]

Hsiao, Y.-S.

S. A. Agemy, N. K. Scripsema, C. M. Shah, T. Chui, P. M. Garcia, J. G. Lee, R. C. Gentile, Y.-S. Hsiao, Q. Zhou, T. Ko, and R. Richard B., “Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients,” Retina 35(11), 2353–2363 (2015).
[Crossref]

Hu, Y.

C. Shen, S. Yan, M. Du, H. Zhao, L. Shao, and Y. Hu, “Assessment of capillary dropout in the superficial retinal capillary plexus by optical coherence tomography angiography in the early stage of diabetic retinopathy,” BMC Ophthalmol. 18(1), 113 (2018).
[Crossref]

Huang, D.

J. J. Yu, A. Camino, L. Liu, X. Zhang, J. Wang, S. S. Gao, Y. Jia, and D. Huang, “Signal strength reduction effects in oct angiography,” Ophthalmol. Retin. 3(10), 835–842 (2019).
[Crossref]

Y. Guo, T. T. Hormel, H. Xiong, B. Wang, A. Camino, J. Wang, D. Huang, T. S. Hwang, and Y. Jia, “Development and validation of a deep learning algorithm for distinguishing the nonperfusion area from signal reduction artifacts on oct angiography,” Biomed. Opt. Express 10(7), 3257–3268 (2019).
[Crossref]

R. C. Patel, J. Wang, T. S. Hwang, M. Zhang, S. S. Gao, M. E. Pennesi, S. T. Bailey, B. J. Lujan, X. Wang, D. J. Wilson, D. Huang, and Y. Jia, “Plexus-specific detection of retinal vascular pathologic conditions with projection-resolved oct angiography,” Ophthalmol. Retin. 2(8), 816–826 (2018).
[Crossref]

T. S. Hwang, A. M. Hagag, J. Wang, M. Zhang, A. Smith, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion areas in 3 vascular plexuses with optical coherence tomography angiography in eyes of patients with diabetes,” JAMA Ophthalmol. 136(8), 929–936 (2018).
[Crossref]

Y. Guo, A. Camino, M. Zhang, J. Wang, D. Huang, T. Hwang, and Y. Jia, “Automated segmentation of retinal layer boundaries and capillary plexuses in wide-field optical coherence tomographic angiography,” Biomed. Opt. Express 9(9), 4429–4442 (2018).
[Crossref]

Y. Guo, A. Camino, J. Wang, D. Huang, T. S. Hwang, and Y. Jia, “Mednet, a neural network for automated detection of avascular area in oct angiography,” Biomed. Opt. Express 9(11), 5147–5158 (2018).
[Crossref]

J. Campbell, M. Zhang, T. Hwang, S. Bailey, D. Wilson, Y. Jia, and D. Huang, “Detailed vascular anatomy of the human retina by projection-resolved optical coherence tomography angiography,” Sci. Rep. 7(1), 42201 (2017).
[Crossref]

J. Wang, M. Zhang, T. S. Hwang, S. T. Bailey, D. Huang, D. J. Wilson, and Y. Jia, “Reflectance-based projection-resolved optical coherence tomography angiography,” Biomed. Opt. Express 8(3), 1536–1548 (2017).
[Crossref]

M. Zhang, T. S. Hwang, C. Dongye, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion in three retinal plexuses using projection-resolved optical coherence tomography angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 57(13), 5101–5106 (2016).
[Crossref]

T. S. Hwang, S. S. Gao, L. Liu, A. K. Lauer, S. T. Bailey, C. J. Flaxel, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of capillary nonperfusion using optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(4), 367–373 (2016).
[Crossref]

T. S. Hwang, M. Zhang, K. Bhavsar, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. K. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Visualization of 3 distinct retinal plexuses by projection-resolved optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
[Crossref]

M. Zhang, T. S. Hwang, J. P. Campbell, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Projection-resolved optical coherence tomographic angiography,” Biomed. Opt. Express 7(3), 816–828 (2016).
[Crossref]

T. S. Hwang, Y. Jia, S. S. Gao, S. T. Bailey, A. K. Lauer, C. J. Flaxel, D. J. Wilson, and D. Huang, “Optical coherence tomography angiography features of diabetic retinopathy,” Retina 35(11), 2371–2376 (2015).
[Crossref]

Y. Jia, S. T. Bailey, T. S. Hwang, S. M. McClintic, S. S. Gao, M. E. Pennesi, C. J. Flaxel, A. K. Lauer, D. J. Wilson, J. Hornegger, J. G. Fujimoto, and D. Huang, “Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye,” Proc. Natl. Acad. Sci. 112(18), E2395–E2402 (2015).
[Crossref]

M. Zhang, J. Wang, A. D. Pechauer, T. S. Hwang, S. S. Gao, L. Liu, L. Liu, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Advanced image processing for optical coherence tomographic angiography of macular diseases,” Biomed. Opt. Express 6(12), 4661–4675 (2015).
[Crossref]

L. Liu, S. S. Gao, S. T. Bailey, D. Huang, D. Li, and Y. Jia, “Automated choroidal neovascularization detection algorithm for optical coherence tomography angiography,” Biomed. Opt. Express 6(9), 3564–3576 (2015).
[Crossref]

Y. Jia, O. Tan, J. Tokayer, B. Potsaid, Y. Wang, J. J. Liu, M. F. Kraus, H. Subhash, J. G. Fujimoto, J. Hornegger, and D. Huang, “Split-spectrum amplitude-decorrelation angiography with optical coherence tomography,” Opt. Express 20(4), 4710–4725 (2012).
[Crossref]

Husvogt, L.

J. Schottenhamml, E. M. Moult, S. Ploner, B. Lee, E. A. Novais, E. Cole, S. Dang, C. D. Lu, L. Husvogt, N. K. Waheed, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “An automatic intercapillary area based algorithm for quantifying diabetes related capillary dropout using oct angiography,” Retina 36, S93–S101 (2016).
[Crossref]

Hwang, T.

Y. Guo, A. Camino, M. Zhang, J. Wang, D. Huang, T. Hwang, and Y. Jia, “Automated segmentation of retinal layer boundaries and capillary plexuses in wide-field optical coherence tomographic angiography,” Biomed. Opt. Express 9(9), 4429–4442 (2018).
[Crossref]

J. Campbell, M. Zhang, T. Hwang, S. Bailey, D. Wilson, Y. Jia, and D. Huang, “Detailed vascular anatomy of the human retina by projection-resolved optical coherence tomography angiography,” Sci. Rep. 7(1), 42201 (2017).
[Crossref]

Hwang, T. S.

Y. Guo, T. T. Hormel, H. Xiong, B. Wang, A. Camino, J. Wang, D. Huang, T. S. Hwang, and Y. Jia, “Development and validation of a deep learning algorithm for distinguishing the nonperfusion area from signal reduction artifacts on oct angiography,” Biomed. Opt. Express 10(7), 3257–3268 (2019).
[Crossref]

R. C. Patel, J. Wang, T. S. Hwang, M. Zhang, S. S. Gao, M. E. Pennesi, S. T. Bailey, B. J. Lujan, X. Wang, D. J. Wilson, D. Huang, and Y. Jia, “Plexus-specific detection of retinal vascular pathologic conditions with projection-resolved oct angiography,” Ophthalmol. Retin. 2(8), 816–826 (2018).
[Crossref]

T. S. Hwang, A. M. Hagag, J. Wang, M. Zhang, A. Smith, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion areas in 3 vascular plexuses with optical coherence tomography angiography in eyes of patients with diabetes,” JAMA Ophthalmol. 136(8), 929–936 (2018).
[Crossref]

Y. Guo, A. Camino, J. Wang, D. Huang, T. S. Hwang, and Y. Jia, “Mednet, a neural network for automated detection of avascular area in oct angiography,” Biomed. Opt. Express 9(11), 5147–5158 (2018).
[Crossref]

J. Wang, M. Zhang, T. S. Hwang, S. T. Bailey, D. Huang, D. J. Wilson, and Y. Jia, “Reflectance-based projection-resolved optical coherence tomography angiography,” Biomed. Opt. Express 8(3), 1536–1548 (2017).
[Crossref]

T. S. Hwang, M. Zhang, K. Bhavsar, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. K. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Visualization of 3 distinct retinal plexuses by projection-resolved optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
[Crossref]

T. S. Hwang, S. S. Gao, L. Liu, A. K. Lauer, S. T. Bailey, C. J. Flaxel, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of capillary nonperfusion using optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(4), 367–373 (2016).
[Crossref]

M. Zhang, T. S. Hwang, C. Dongye, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion in three retinal plexuses using projection-resolved optical coherence tomography angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 57(13), 5101–5106 (2016).
[Crossref]

M. Zhang, T. S. Hwang, J. P. Campbell, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Projection-resolved optical coherence tomographic angiography,” Biomed. Opt. Express 7(3), 816–828 (2016).
[Crossref]

Y. Jia, S. T. Bailey, T. S. Hwang, S. M. McClintic, S. S. Gao, M. E. Pennesi, C. J. Flaxel, A. K. Lauer, D. J. Wilson, J. Hornegger, J. G. Fujimoto, and D. Huang, “Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye,” Proc. Natl. Acad. Sci. 112(18), E2395–E2402 (2015).
[Crossref]

T. S. Hwang, Y. Jia, S. S. Gao, S. T. Bailey, A. K. Lauer, C. J. Flaxel, D. J. Wilson, and D. Huang, “Optical coherence tomography angiography features of diabetic retinopathy,” Retina 35(11), 2371–2376 (2015).
[Crossref]

M. Zhang, J. Wang, A. D. Pechauer, T. S. Hwang, S. S. Gao, L. Liu, L. Liu, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Advanced image processing for optical coherence tomographic angiography of macular diseases,” Biomed. Opt. Express 6(12), 4661–4675 (2015).
[Crossref]

Ishibazawa, A.

A. Ishibazawa, T. Nagaoka, A. Takahashi, T. Omae, T. Tani, K. Sogawa, H. Yokota, and A. Yoshida, “Optical coherence tomography angiography in diabetic retinopathy: a prospective pilot study,” Am. J. Ophthalmol. 160(1), 35–44.e1 (2015).
[Crossref]

Jampol, L. M.

A. C. Onishi, P. L. Nesper, P. K. Roberts, G. A. Moharram, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Importance of considering the middle capillary plexus on oct angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 59(5), 2167–2176 (2018).
[Crossref]

P. L. Nesper, P. K. Roberts, A. C. Onishi, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Quantifying microvascular abnormalities with increasing severity of diabetic retinopathy using optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 58(6), BIO307 (2017).
[Crossref]

Jia, Y.

J. J. Yu, A. Camino, L. Liu, X. Zhang, J. Wang, S. S. Gao, Y. Jia, and D. Huang, “Signal strength reduction effects in oct angiography,” Ophthalmol. Retin. 3(10), 835–842 (2019).
[Crossref]

Y. Guo, T. T. Hormel, H. Xiong, B. Wang, A. Camino, J. Wang, D. Huang, T. S. Hwang, and Y. Jia, “Development and validation of a deep learning algorithm for distinguishing the nonperfusion area from signal reduction artifacts on oct angiography,” Biomed. Opt. Express 10(7), 3257–3268 (2019).
[Crossref]

R. C. Patel, J. Wang, T. S. Hwang, M. Zhang, S. S. Gao, M. E. Pennesi, S. T. Bailey, B. J. Lujan, X. Wang, D. J. Wilson, D. Huang, and Y. Jia, “Plexus-specific detection of retinal vascular pathologic conditions with projection-resolved oct angiography,” Ophthalmol. Retin. 2(8), 816–826 (2018).
[Crossref]

T. S. Hwang, A. M. Hagag, J. Wang, M. Zhang, A. Smith, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion areas in 3 vascular plexuses with optical coherence tomography angiography in eyes of patients with diabetes,” JAMA Ophthalmol. 136(8), 929–936 (2018).
[Crossref]

Y. Guo, A. Camino, M. Zhang, J. Wang, D. Huang, T. Hwang, and Y. Jia, “Automated segmentation of retinal layer boundaries and capillary plexuses in wide-field optical coherence tomographic angiography,” Biomed. Opt. Express 9(9), 4429–4442 (2018).
[Crossref]

Y. Guo, A. Camino, J. Wang, D. Huang, T. S. Hwang, and Y. Jia, “Mednet, a neural network for automated detection of avascular area in oct angiography,” Biomed. Opt. Express 9(11), 5147–5158 (2018).
[Crossref]

J. Campbell, M. Zhang, T. Hwang, S. Bailey, D. Wilson, Y. Jia, and D. Huang, “Detailed vascular anatomy of the human retina by projection-resolved optical coherence tomography angiography,” Sci. Rep. 7(1), 42201 (2017).
[Crossref]

J. Wang, M. Zhang, T. S. Hwang, S. T. Bailey, D. Huang, D. J. Wilson, and Y. Jia, “Reflectance-based projection-resolved optical coherence tomography angiography,” Biomed. Opt. Express 8(3), 1536–1548 (2017).
[Crossref]

M. Zhang, T. S. Hwang, C. Dongye, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion in three retinal plexuses using projection-resolved optical coherence tomography angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 57(13), 5101–5106 (2016).
[Crossref]

T. S. Hwang, S. S. Gao, L. Liu, A. K. Lauer, S. T. Bailey, C. J. Flaxel, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of capillary nonperfusion using optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(4), 367–373 (2016).
[Crossref]

T. S. Hwang, M. Zhang, K. Bhavsar, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. K. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Visualization of 3 distinct retinal plexuses by projection-resolved optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
[Crossref]

M. Zhang, T. S. Hwang, J. P. Campbell, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Projection-resolved optical coherence tomographic angiography,” Biomed. Opt. Express 7(3), 816–828 (2016).
[Crossref]

Y. Jia, S. T. Bailey, T. S. Hwang, S. M. McClintic, S. S. Gao, M. E. Pennesi, C. J. Flaxel, A. K. Lauer, D. J. Wilson, J. Hornegger, J. G. Fujimoto, and D. Huang, “Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye,” Proc. Natl. Acad. Sci. 112(18), E2395–E2402 (2015).
[Crossref]

T. S. Hwang, Y. Jia, S. S. Gao, S. T. Bailey, A. K. Lauer, C. J. Flaxel, D. J. Wilson, and D. Huang, “Optical coherence tomography angiography features of diabetic retinopathy,” Retina 35(11), 2371–2376 (2015).
[Crossref]

M. Zhang, J. Wang, A. D. Pechauer, T. S. Hwang, S. S. Gao, L. Liu, L. Liu, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Advanced image processing for optical coherence tomographic angiography of macular diseases,” Biomed. Opt. Express 6(12), 4661–4675 (2015).
[Crossref]

L. Liu, S. S. Gao, S. T. Bailey, D. Huang, D. Li, and Y. Jia, “Automated choroidal neovascularization detection algorithm for optical coherence tomography angiography,” Biomed. Opt. Express 6(9), 3564–3576 (2015).
[Crossref]

Y. Jia, O. Tan, J. Tokayer, B. Potsaid, Y. Wang, J. J. Liu, M. F. Kraus, H. Subhash, J. G. Fujimoto, J. Hornegger, and D. Huang, “Split-spectrum amplitude-decorrelation angiography with optical coherence tomography,” Opt. Express 20(4), 4710–4725 (2012).
[Crossref]

Karampelas, M.

D. A. Sim, P. A. Keane, S. Fung, M. Karampelas, S. R. Sadda, M. Fruttiger, P. J. Patel, A. Tufail, and C. A. Egan, “Quantitative analysis of diabetic macular ischemia using optical coherence tomography,” Invest. Ophthalmol. Visual Sci. 55(1), 417–423 (2014).
[Crossref]

Keane, P. A.

D. A. Sim, P. A. Keane, S. Fung, M. Karampelas, S. R. Sadda, M. Fruttiger, P. J. Patel, A. Tufail, and C. A. Egan, “Quantitative analysis of diabetic macular ischemia using optical coherence tomography,” Invest. Ophthalmol. Visual Sci. 55(1), 417–423 (2014).
[Crossref]

Kiss, S.

M. M. Wessel, N. Nair, G. D. Aaker, J. R. Ehrlich, D. J. D’Amico, and S. Kiss, “Peripheral retinal ischaemia, as evaluated by ultra-widefield fluorescein angiography, is associated with diabetic macular oedema,” Br. J. Ophthalmol. 96(5), 694–698 (2012).
[Crossref]

Klein, B. E.

R. Klein, B. E. Klein, S. E. Moss, M. D. Davis, and D. L. DeMets, “The wisconsin epidemiologic study of diabetic retinopathy: Ii. prevalence and risk of diabetic retinopathy when age at diagnosis is less than 30 years,” Arch. Ophthalmol. 102(4), 520–526 (1984).
[Crossref]

Klein, R.

R. Klein, B. E. Klein, S. E. Moss, M. D. Davis, and D. L. DeMets, “The wisconsin epidemiologic study of diabetic retinopathy: Ii. prevalence and risk of diabetic retinopathy when age at diagnosis is less than 30 years,” Arch. Ophthalmol. 102(4), 520–526 (1984).
[Crossref]

Ko, T.

S. A. Agemy, N. K. Scripsema, C. M. Shah, T. Chui, P. M. Garcia, J. G. Lee, R. C. Gentile, Y.-S. Hsiao, Q. Zhou, T. Ko, and R. Richard B., “Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients,” Retina 35(11), 2353–2363 (2015).
[Crossref]

Kraus, M. F.

Lauer, A. K.

T. S. Hwang, S. S. Gao, L. Liu, A. K. Lauer, S. T. Bailey, C. J. Flaxel, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of capillary nonperfusion using optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(4), 367–373 (2016).
[Crossref]

T. S. Hwang, M. Zhang, K. Bhavsar, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. K. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Visualization of 3 distinct retinal plexuses by projection-resolved optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
[Crossref]

T. S. Hwang, Y. Jia, S. S. Gao, S. T. Bailey, A. K. Lauer, C. J. Flaxel, D. J. Wilson, and D. Huang, “Optical coherence tomography angiography features of diabetic retinopathy,” Retina 35(11), 2371–2376 (2015).
[Crossref]

Y. Jia, S. T. Bailey, T. S. Hwang, S. M. McClintic, S. S. Gao, M. E. Pennesi, C. J. Flaxel, A. K. Lauer, D. J. Wilson, J. Hornegger, J. G. Fujimoto, and D. Huang, “Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye,” Proc. Natl. Acad. Sci. 112(18), E2395–E2402 (2015).
[Crossref]

Lee, B.

J. Schottenhamml, E. M. Moult, S. Ploner, B. Lee, E. A. Novais, E. Cole, S. Dang, C. D. Lu, L. Husvogt, N. K. Waheed, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “An automatic intercapillary area based algorithm for quantifying diabetes related capillary dropout using oct angiography,” Retina 36, S93–S101 (2016).
[Crossref]

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

Lee, J. G.

S. A. Agemy, N. K. Scripsema, C. M. Shah, T. Chui, P. M. Garcia, J. G. Lee, R. C. Gentile, Y.-S. Hsiao, Q. Zhou, T. Ko, and R. Richard B., “Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients,” Retina 35(11), 2353–2363 (2015).
[Crossref]

Li, D.

Lin, D. Y.

D. Y. Lin, M. S. Blumenkranz, R. J. Brothers, D. M. Grosvenor, and T. D. D. S. Group, “The sensitivity and specificity of single-field nonmydriatic monochromatic digital fundus photography with remote image interpretation for diabetic retinopathy screening: a comparison with ophthalmoscopy and standardized mydriatic color photography,” Am. J. Ophthalmol. 134(2), 204–213 (2002).
[Crossref]

Lin, P.

T. S. Hwang, M. Zhang, K. Bhavsar, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. K. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Visualization of 3 distinct retinal plexuses by projection-resolved optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
[Crossref]

Liu, J. J.

Liu, L.

J. J. Yu, A. Camino, L. Liu, X. Zhang, J. Wang, S. S. Gao, Y. Jia, and D. Huang, “Signal strength reduction effects in oct angiography,” Ophthalmol. Retin. 3(10), 835–842 (2019).
[Crossref]

A. C. Onishi, P. L. Nesper, P. K. Roberts, G. A. Moharram, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Importance of considering the middle capillary plexus on oct angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 59(5), 2167–2176 (2018).
[Crossref]

P. L. Nesper, P. K. Roberts, A. C. Onishi, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Quantifying microvascular abnormalities with increasing severity of diabetic retinopathy using optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 58(6), BIO307 (2017).
[Crossref]

T. S. Hwang, S. S. Gao, L. Liu, A. K. Lauer, S. T. Bailey, C. J. Flaxel, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of capillary nonperfusion using optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(4), 367–373 (2016).
[Crossref]

M. Zhang, J. Wang, A. D. Pechauer, T. S. Hwang, S. S. Gao, L. Liu, L. Liu, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Advanced image processing for optical coherence tomographic angiography of macular diseases,” Biomed. Opt. Express 6(12), 4661–4675 (2015).
[Crossref]

M. Zhang, J. Wang, A. D. Pechauer, T. S. Hwang, S. S. Gao, L. Liu, L. Liu, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Advanced image processing for optical coherence tomographic angiography of macular diseases,” Biomed. Opt. Express 6(12), 4661–4675 (2015).
[Crossref]

L. Liu, S. S. Gao, S. T. Bailey, D. Huang, D. Li, and Y. Jia, “Automated choroidal neovascularization detection algorithm for optical coherence tomography angiography,” Biomed. Opt. Express 6(9), 3564–3576 (2015).
[Crossref]

Lu, C. D.

J. Schottenhamml, E. M. Moult, S. Ploner, B. Lee, E. A. Novais, E. Cole, S. Dang, C. D. Lu, L. Husvogt, N. K. Waheed, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “An automatic intercapillary area based algorithm for quantifying diabetes related capillary dropout using oct angiography,” Retina 36, S93–S101 (2016).
[Crossref]

Lujan, B. J.

R. C. Patel, J. Wang, T. S. Hwang, M. Zhang, S. S. Gao, M. E. Pennesi, S. T. Bailey, B. J. Lujan, X. Wang, D. J. Wilson, D. Huang, and Y. Jia, “Plexus-specific detection of retinal vascular pathologic conditions with projection-resolved oct angiography,” Ophthalmol. Retin. 2(8), 816–826 (2018).
[Crossref]

Mayer, M. A.

McClintic, S. M.

Y. Jia, S. T. Bailey, T. S. Hwang, S. M. McClintic, S. S. Gao, M. E. Pennesi, C. J. Flaxel, A. K. Lauer, D. J. Wilson, J. Hornegger, J. G. Fujimoto, and D. Huang, “Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye,” Proc. Natl. Acad. Sci. 112(18), E2395–E2402 (2015).
[Crossref]

McGowan, M.

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

Moharram, G. A.

A. C. Onishi, P. L. Nesper, P. K. Roberts, G. A. Moharram, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Importance of considering the middle capillary plexus on oct angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 59(5), 2167–2176 (2018).
[Crossref]

Morino, K.

K. Morino, T. Murakami, Y. Dodo, S. Yasukura, T. Yoshitake, M. Fujimoto, and A. Tsujikawa, “Characteristics of diabetic capillary nonperfusion in macular and extramacular white spots on optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 60(5), 1595–1603 (2019).
[Crossref]

Moss, S. E.

R. Klein, B. E. Klein, S. E. Moss, M. D. Davis, and D. L. DeMets, “The wisconsin epidemiologic study of diabetic retinopathy: Ii. prevalence and risk of diabetic retinopathy when age at diagnosis is less than 30 years,” Arch. Ophthalmol. 102(4), 520–526 (1984).
[Crossref]

Moult, E. M.

J. Schottenhamml, E. M. Moult, S. Ploner, B. Lee, E. A. Novais, E. Cole, S. Dang, C. D. Lu, L. Husvogt, N. K. Waheed, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “An automatic intercapillary area based algorithm for quantifying diabetes related capillary dropout using oct angiography,” Retina 36, S93–S101 (2016).
[Crossref]

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

Murakami, T.

K. Morino, T. Murakami, Y. Dodo, S. Yasukura, T. Yoshitake, M. Fujimoto, and A. Tsujikawa, “Characteristics of diabetic capillary nonperfusion in macular and extramacular white spots on optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 60(5), 1595–1603 (2019).
[Crossref]

Nagaoka, T.

A. Ishibazawa, T. Nagaoka, A. Takahashi, T. Omae, T. Tani, K. Sogawa, H. Yokota, and A. Yoshida, “Optical coherence tomography angiography in diabetic retinopathy: a prospective pilot study,” Am. J. Ophthalmol. 160(1), 35–44.e1 (2015).
[Crossref]

Nair, N.

M. M. Wessel, N. Nair, G. D. Aaker, J. R. Ehrlich, D. J. D’Amico, and S. Kiss, “Peripheral retinal ischaemia, as evaluated by ultra-widefield fluorescein angiography, is associated with diabetic macular oedema,” Br. J. Ophthalmol. 96(5), 694–698 (2012).
[Crossref]

Nesper, P. L.

A. C. Onishi, P. L. Nesper, P. K. Roberts, G. A. Moharram, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Importance of considering the middle capillary plexus on oct angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 59(5), 2167–2176 (2018).
[Crossref]

P. L. Nesper, P. K. Roberts, A. C. Onishi, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Quantifying microvascular abnormalities with increasing severity of diabetic retinopathy using optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 58(6), BIO307 (2017).
[Crossref]

Noma, H.

K. Sakata, H. Funatsu, S. Harino, H. Noma, and S. Hori, “Relationship between macular microcirculation and progression of diabetic macular edema,” Ophthalmology 113(8), 1385–1391 (2006).
[Crossref]

Novais, E. A.

J. Schottenhamml, E. M. Moult, S. Ploner, B. Lee, E. A. Novais, E. Cole, S. Dang, C. D. Lu, L. Husvogt, N. K. Waheed, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “An automatic intercapillary area based algorithm for quantifying diabetes related capillary dropout using oct angiography,” Retina 36, S93–S101 (2016).
[Crossref]

Omae, T.

A. Ishibazawa, T. Nagaoka, A. Takahashi, T. Omae, T. Tani, K. Sogawa, H. Yokota, and A. Yoshida, “Optical coherence tomography angiography in diabetic retinopathy: a prospective pilot study,” Am. J. Ophthalmol. 160(1), 35–44.e1 (2015).
[Crossref]

Onishi, A. C.

A. C. Onishi, P. L. Nesper, P. K. Roberts, G. A. Moharram, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Importance of considering the middle capillary plexus on oct angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 59(5), 2167–2176 (2018).
[Crossref]

P. L. Nesper, P. K. Roberts, A. C. Onishi, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Quantifying microvascular abnormalities with increasing severity of diabetic retinopathy using optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 58(6), BIO307 (2017).
[Crossref]

Or, C.

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

Park, J. J.

J. J. Park, C. S. Chung, and A. A. Fawzi, “Visualizing structure and vascular interactions: macular nonperfusion in three capillary plexuses,” Ophthalmic Surgery, Lasers Imaging Retin. 49(11), e182–e190 (2018).
[Crossref]

Patel, P. J.

D. A. Sim, P. A. Keane, S. Fung, M. Karampelas, S. R. Sadda, M. Fruttiger, P. J. Patel, A. Tufail, and C. A. Egan, “Quantitative analysis of diabetic macular ischemia using optical coherence tomography,” Invest. Ophthalmol. Visual Sci. 55(1), 417–423 (2014).
[Crossref]

Patel, R. C.

R. C. Patel, J. Wang, T. S. Hwang, M. Zhang, S. S. Gao, M. E. Pennesi, S. T. Bailey, B. J. Lujan, X. Wang, D. J. Wilson, D. Huang, and Y. Jia, “Plexus-specific detection of retinal vascular pathologic conditions with projection-resolved oct angiography,” Ophthalmol. Retin. 2(8), 816–826 (2018).
[Crossref]

Pechauer, A. D.

Pennesi, M. E.

R. C. Patel, J. Wang, T. S. Hwang, M. Zhang, S. S. Gao, M. E. Pennesi, S. T. Bailey, B. J. Lujan, X. Wang, D. J. Wilson, D. Huang, and Y. Jia, “Plexus-specific detection of retinal vascular pathologic conditions with projection-resolved oct angiography,” Ophthalmol. Retin. 2(8), 816–826 (2018).
[Crossref]

Y. Jia, S. T. Bailey, T. S. Hwang, S. M. McClintic, S. S. Gao, M. E. Pennesi, C. J. Flaxel, A. K. Lauer, D. J. Wilson, J. Hornegger, J. G. Fujimoto, and D. Huang, “Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye,” Proc. Natl. Acad. Sci. 112(18), E2395–E2402 (2015).
[Crossref]

Ploner, S.

J. Schottenhamml, E. M. Moult, S. Ploner, B. Lee, E. A. Novais, E. Cole, S. Dang, C. D. Lu, L. Husvogt, N. K. Waheed, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “An automatic intercapillary area based algorithm for quantifying diabetes related capillary dropout using oct angiography,” Retina 36, S93–S101 (2016).
[Crossref]

Potsaid, B.

Reichel, E.

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

Richard B., R.

S. A. Agemy, N. K. Scripsema, C. M. Shah, T. Chui, P. M. Garcia, J. G. Lee, R. C. Gentile, Y.-S. Hsiao, Q. Zhou, T. Ko, and R. Richard B., “Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients,” Retina 35(11), 2353–2363 (2015).
[Crossref]

Roberts, P. K.

A. C. Onishi, P. L. Nesper, P. K. Roberts, G. A. Moharram, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Importance of considering the middle capillary plexus on oct angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 59(5), 2167–2176 (2018).
[Crossref]

P. L. Nesper, P. K. Roberts, A. C. Onishi, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Quantifying microvascular abnormalities with increasing severity of diabetic retinopathy using optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 58(6), BIO307 (2017).
[Crossref]

S. Group, T. D. D.

D. Y. Lin, M. S. Blumenkranz, R. J. Brothers, D. M. Grosvenor, and T. D. D. S. Group, “The sensitivity and specificity of single-field nonmydriatic monochromatic digital fundus photography with remote image interpretation for diabetic retinopathy screening: a comparison with ophthalmoscopy and standardized mydriatic color photography,” Am. J. Ophthalmol. 134(2), 204–213 (2002).
[Crossref]

Sadda, S. R.

D. A. Sim, P. A. Keane, S. Fung, M. Karampelas, S. R. Sadda, M. Fruttiger, P. J. Patel, A. Tufail, and C. A. Egan, “Quantitative analysis of diabetic macular ischemia using optical coherence tomography,” Invest. Ophthalmol. Visual Sci. 55(1), 417–423 (2014).
[Crossref]

Sakata, K.

K. Sakata, H. Funatsu, S. Harino, H. Noma, and S. Hori, “Relationship between macular microcirculation and progression of diabetic macular edema,” Ophthalmology 113(8), 1385–1391 (2006).
[Crossref]

Schottenhamml, J.

J. Schottenhamml, E. M. Moult, S. Ploner, B. Lee, E. A. Novais, E. Cole, S. Dang, C. D. Lu, L. Husvogt, N. K. Waheed, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “An automatic intercapillary area based algorithm for quantifying diabetes related capillary dropout using oct angiography,” Retina 36, S93–S101 (2016).
[Crossref]

Scripsema, N. K.

S. A. Agemy, N. K. Scripsema, C. M. Shah, T. Chui, P. M. Garcia, J. G. Lee, R. C. Gentile, Y.-S. Hsiao, Q. Zhou, T. Ko, and R. Richard B., “Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients,” Retina 35(11), 2353–2363 (2015).
[Crossref]

Shah, C. M.

S. A. Agemy, N. K. Scripsema, C. M. Shah, T. Chui, P. M. Garcia, J. G. Lee, R. C. Gentile, Y.-S. Hsiao, Q. Zhou, T. Ko, and R. Richard B., “Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients,” Retina 35(11), 2353–2363 (2015).
[Crossref]

Shao, L.

C. Shen, S. Yan, M. Du, H. Zhao, L. Shao, and Y. Hu, “Assessment of capillary dropout in the superficial retinal capillary plexus by optical coherence tomography angiography in the early stage of diabetic retinopathy,” BMC Ophthalmol. 18(1), 113 (2018).
[Crossref]

Shen, C.

C. Shen, S. Yan, M. Du, H. Zhao, L. Shao, and Y. Hu, “Assessment of capillary dropout in the superficial retinal capillary plexus by optical coherence tomography angiography in the early stage of diabetic retinopathy,” BMC Ophthalmol. 18(1), 113 (2018).
[Crossref]

Sim, D. A.

D. A. Sim, P. A. Keane, S. Fung, M. Karampelas, S. R. Sadda, M. Fruttiger, P. J. Patel, A. Tufail, and C. A. Egan, “Quantitative analysis of diabetic macular ischemia using optical coherence tomography,” Invest. Ophthalmol. Visual Sci. 55(1), 417–423 (2014).
[Crossref]

Smith, A.

T. S. Hwang, A. M. Hagag, J. Wang, M. Zhang, A. Smith, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion areas in 3 vascular plexuses with optical coherence tomography angiography in eyes of patients with diabetes,” JAMA Ophthalmol. 136(8), 929–936 (2018).
[Crossref]

Sogawa, K.

A. Ishibazawa, T. Nagaoka, A. Takahashi, T. Omae, T. Tani, K. Sogawa, H. Yokota, and A. Yoshida, “Optical coherence tomography angiography in diabetic retinopathy: a prospective pilot study,” Am. J. Ophthalmol. 160(1), 35–44.e1 (2015).
[Crossref]

Subhash, H.

Takahashi, A.

A. Ishibazawa, T. Nagaoka, A. Takahashi, T. Omae, T. Tani, K. Sogawa, H. Yokota, and A. Yoshida, “Optical coherence tomography angiography in diabetic retinopathy: a prospective pilot study,” Am. J. Ophthalmol. 160(1), 35–44.e1 (2015).
[Crossref]

Tan, O.

Tani, T.

A. Ishibazawa, T. Nagaoka, A. Takahashi, T. Omae, T. Tani, K. Sogawa, H. Yokota, and A. Yoshida, “Optical coherence tomography angiography in diabetic retinopathy: a prospective pilot study,” Am. J. Ophthalmol. 160(1), 35–44.e1 (2015).
[Crossref]

Tokayer, J.

Tsujikawa, A.

K. Morino, T. Murakami, Y. Dodo, S. Yasukura, T. Yoshitake, M. Fujimoto, and A. Tsujikawa, “Characteristics of diabetic capillary nonperfusion in macular and extramacular white spots on optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 60(5), 1595–1603 (2019).
[Crossref]

Tufail, A.

D. A. Sim, P. A. Keane, S. Fung, M. Karampelas, S. R. Sadda, M. Fruttiger, P. J. Patel, A. Tufail, and C. A. Egan, “Quantitative analysis of diabetic macular ischemia using optical coherence tomography,” Invest. Ophthalmol. Visual Sci. 55(1), 417–423 (2014).
[Crossref]

Waheed, N. K.

J. Schottenhamml, E. M. Moult, S. Ploner, B. Lee, E. A. Novais, E. Cole, S. Dang, C. D. Lu, L. Husvogt, N. K. Waheed, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “An automatic intercapillary area based algorithm for quantifying diabetes related capillary dropout using oct angiography,” Retina 36, S93–S101 (2016).
[Crossref]

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

Wang, B.

Wang, J.

Y. Guo, T. T. Hormel, H. Xiong, B. Wang, A. Camino, J. Wang, D. Huang, T. S. Hwang, and Y. Jia, “Development and validation of a deep learning algorithm for distinguishing the nonperfusion area from signal reduction artifacts on oct angiography,” Biomed. Opt. Express 10(7), 3257–3268 (2019).
[Crossref]

J. J. Yu, A. Camino, L. Liu, X. Zhang, J. Wang, S. S. Gao, Y. Jia, and D. Huang, “Signal strength reduction effects in oct angiography,” Ophthalmol. Retin. 3(10), 835–842 (2019).
[Crossref]

R. C. Patel, J. Wang, T. S. Hwang, M. Zhang, S. S. Gao, M. E. Pennesi, S. T. Bailey, B. J. Lujan, X. Wang, D. J. Wilson, D. Huang, and Y. Jia, “Plexus-specific detection of retinal vascular pathologic conditions with projection-resolved oct angiography,” Ophthalmol. Retin. 2(8), 816–826 (2018).
[Crossref]

T. S. Hwang, A. M. Hagag, J. Wang, M. Zhang, A. Smith, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion areas in 3 vascular plexuses with optical coherence tomography angiography in eyes of patients with diabetes,” JAMA Ophthalmol. 136(8), 929–936 (2018).
[Crossref]

Y. Guo, A. Camino, M. Zhang, J. Wang, D. Huang, T. Hwang, and Y. Jia, “Automated segmentation of retinal layer boundaries and capillary plexuses in wide-field optical coherence tomographic angiography,” Biomed. Opt. Express 9(9), 4429–4442 (2018).
[Crossref]

Y. Guo, A. Camino, J. Wang, D. Huang, T. S. Hwang, and Y. Jia, “Mednet, a neural network for automated detection of avascular area in oct angiography,” Biomed. Opt. Express 9(11), 5147–5158 (2018).
[Crossref]

J. Wang, M. Zhang, T. S. Hwang, S. T. Bailey, D. Huang, D. J. Wilson, and Y. Jia, “Reflectance-based projection-resolved optical coherence tomography angiography,” Biomed. Opt. Express 8(3), 1536–1548 (2017).
[Crossref]

M. Zhang, J. Wang, A. D. Pechauer, T. S. Hwang, S. S. Gao, L. Liu, L. Liu, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Advanced image processing for optical coherence tomographic angiography of macular diseases,” Biomed. Opt. Express 6(12), 4661–4675 (2015).
[Crossref]

Wang, X.

R. C. Patel, J. Wang, T. S. Hwang, M. Zhang, S. S. Gao, M. E. Pennesi, S. T. Bailey, B. J. Lujan, X. Wang, D. J. Wilson, D. Huang, and Y. Jia, “Plexus-specific detection of retinal vascular pathologic conditions with projection-resolved oct angiography,” Ophthalmol. Retin. 2(8), 816–826 (2018).
[Crossref]

Wang, Y.

Wessel, M. M.

M. M. Wessel, N. Nair, G. D. Aaker, J. R. Ehrlich, D. J. D’Amico, and S. Kiss, “Peripheral retinal ischaemia, as evaluated by ultra-widefield fluorescein angiography, is associated with diabetic macular oedema,” Br. J. Ophthalmol. 96(5), 694–698 (2012).
[Crossref]

Wilson, D.

J. Campbell, M. Zhang, T. Hwang, S. Bailey, D. Wilson, Y. Jia, and D. Huang, “Detailed vascular anatomy of the human retina by projection-resolved optical coherence tomography angiography,” Sci. Rep. 7(1), 42201 (2017).
[Crossref]

Wilson, D. J.

R. C. Patel, J. Wang, T. S. Hwang, M. Zhang, S. S. Gao, M. E. Pennesi, S. T. Bailey, B. J. Lujan, X. Wang, D. J. Wilson, D. Huang, and Y. Jia, “Plexus-specific detection of retinal vascular pathologic conditions with projection-resolved oct angiography,” Ophthalmol. Retin. 2(8), 816–826 (2018).
[Crossref]

T. S. Hwang, A. M. Hagag, J. Wang, M. Zhang, A. Smith, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion areas in 3 vascular plexuses with optical coherence tomography angiography in eyes of patients with diabetes,” JAMA Ophthalmol. 136(8), 929–936 (2018).
[Crossref]

J. Wang, M. Zhang, T. S. Hwang, S. T. Bailey, D. Huang, D. J. Wilson, and Y. Jia, “Reflectance-based projection-resolved optical coherence tomography angiography,” Biomed. Opt. Express 8(3), 1536–1548 (2017).
[Crossref]

T. S. Hwang, M. Zhang, K. Bhavsar, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. K. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Visualization of 3 distinct retinal plexuses by projection-resolved optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
[Crossref]

T. S. Hwang, S. S. Gao, L. Liu, A. K. Lauer, S. T. Bailey, C. J. Flaxel, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of capillary nonperfusion using optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(4), 367–373 (2016).
[Crossref]

M. Zhang, T. S. Hwang, C. Dongye, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion in three retinal plexuses using projection-resolved optical coherence tomography angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 57(13), 5101–5106 (2016).
[Crossref]

M. Zhang, T. S. Hwang, J. P. Campbell, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Projection-resolved optical coherence tomographic angiography,” Biomed. Opt. Express 7(3), 816–828 (2016).
[Crossref]

Y. Jia, S. T. Bailey, T. S. Hwang, S. M. McClintic, S. S. Gao, M. E. Pennesi, C. J. Flaxel, A. K. Lauer, D. J. Wilson, J. Hornegger, J. G. Fujimoto, and D. Huang, “Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye,” Proc. Natl. Acad. Sci. 112(18), E2395–E2402 (2015).
[Crossref]

T. S. Hwang, Y. Jia, S. S. Gao, S. T. Bailey, A. K. Lauer, C. J. Flaxel, D. J. Wilson, and D. Huang, “Optical coherence tomography angiography features of diabetic retinopathy,” Retina 35(11), 2371–2376 (2015).
[Crossref]

M. Zhang, J. Wang, A. D. Pechauer, T. S. Hwang, S. S. Gao, L. Liu, L. Liu, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Advanced image processing for optical coherence tomographic angiography of macular diseases,” Biomed. Opt. Express 6(12), 4661–4675 (2015).
[Crossref]

Witkin, A. J.

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

Xiong, H.

Yan, S.

C. Shen, S. Yan, M. Du, H. Zhao, L. Shao, and Y. Hu, “Assessment of capillary dropout in the superficial retinal capillary plexus by optical coherence tomography angiography in the early stage of diabetic retinopathy,” BMC Ophthalmol. 18(1), 113 (2018).
[Crossref]

Yasukura, S.

K. Morino, T. Murakami, Y. Dodo, S. Yasukura, T. Yoshitake, M. Fujimoto, and A. Tsujikawa, “Characteristics of diabetic capillary nonperfusion in macular and extramacular white spots on optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 60(5), 1595–1603 (2019).
[Crossref]

Yokota, H.

A. Ishibazawa, T. Nagaoka, A. Takahashi, T. Omae, T. Tani, K. Sogawa, H. Yokota, and A. Yoshida, “Optical coherence tomography angiography in diabetic retinopathy: a prospective pilot study,” Am. J. Ophthalmol. 160(1), 35–44.e1 (2015).
[Crossref]

Yoshida, A.

A. Ishibazawa, T. Nagaoka, A. Takahashi, T. Omae, T. Tani, K. Sogawa, H. Yokota, and A. Yoshida, “Optical coherence tomography angiography in diabetic retinopathy: a prospective pilot study,” Am. J. Ophthalmol. 160(1), 35–44.e1 (2015).
[Crossref]

Yoshitake, T.

K. Morino, T. Murakami, Y. Dodo, S. Yasukura, T. Yoshitake, M. Fujimoto, and A. Tsujikawa, “Characteristics of diabetic capillary nonperfusion in macular and extramacular white spots on optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 60(5), 1595–1603 (2019).
[Crossref]

Yu, J. J.

J. J. Yu, A. Camino, L. Liu, X. Zhang, J. Wang, S. S. Gao, Y. Jia, and D. Huang, “Signal strength reduction effects in oct angiography,” Ophthalmol. Retin. 3(10), 835–842 (2019).
[Crossref]

Zhang, M.

R. C. Patel, J. Wang, T. S. Hwang, M. Zhang, S. S. Gao, M. E. Pennesi, S. T. Bailey, B. J. Lujan, X. Wang, D. J. Wilson, D. Huang, and Y. Jia, “Plexus-specific detection of retinal vascular pathologic conditions with projection-resolved oct angiography,” Ophthalmol. Retin. 2(8), 816–826 (2018).
[Crossref]

T. S. Hwang, A. M. Hagag, J. Wang, M. Zhang, A. Smith, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion areas in 3 vascular plexuses with optical coherence tomography angiography in eyes of patients with diabetes,” JAMA Ophthalmol. 136(8), 929–936 (2018).
[Crossref]

Y. Guo, A. Camino, M. Zhang, J. Wang, D. Huang, T. Hwang, and Y. Jia, “Automated segmentation of retinal layer boundaries and capillary plexuses in wide-field optical coherence tomographic angiography,” Biomed. Opt. Express 9(9), 4429–4442 (2018).
[Crossref]

J. Campbell, M. Zhang, T. Hwang, S. Bailey, D. Wilson, Y. Jia, and D. Huang, “Detailed vascular anatomy of the human retina by projection-resolved optical coherence tomography angiography,” Sci. Rep. 7(1), 42201 (2017).
[Crossref]

J. Wang, M. Zhang, T. S. Hwang, S. T. Bailey, D. Huang, D. J. Wilson, and Y. Jia, “Reflectance-based projection-resolved optical coherence tomography angiography,” Biomed. Opt. Express 8(3), 1536–1548 (2017).
[Crossref]

M. Zhang, T. S. Hwang, C. Dongye, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion in three retinal plexuses using projection-resolved optical coherence tomography angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 57(13), 5101–5106 (2016).
[Crossref]

T. S. Hwang, M. Zhang, K. Bhavsar, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. K. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Visualization of 3 distinct retinal plexuses by projection-resolved optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
[Crossref]

M. Zhang, T. S. Hwang, J. P. Campbell, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Projection-resolved optical coherence tomographic angiography,” Biomed. Opt. Express 7(3), 816–828 (2016).
[Crossref]

M. Zhang, J. Wang, A. D. Pechauer, T. S. Hwang, S. S. Gao, L. Liu, L. Liu, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Advanced image processing for optical coherence tomographic angiography of macular diseases,” Biomed. Opt. Express 6(12), 4661–4675 (2015).
[Crossref]

Zhang, X.

J. J. Yu, A. Camino, L. Liu, X. Zhang, J. Wang, S. S. Gao, Y. Jia, and D. Huang, “Signal strength reduction effects in oct angiography,” Ophthalmol. Retin. 3(10), 835–842 (2019).
[Crossref]

T. S. Hwang, M. Zhang, K. Bhavsar, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. K. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Visualization of 3 distinct retinal plexuses by projection-resolved optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
[Crossref]

Zhao, H.

C. Shen, S. Yan, M. Du, H. Zhao, L. Shao, and Y. Hu, “Assessment of capillary dropout in the superficial retinal capillary plexus by optical coherence tomography angiography in the early stage of diabetic retinopathy,” BMC Ophthalmol. 18(1), 113 (2018).
[Crossref]

Zhou, Q.

S. A. Agemy, N. K. Scripsema, C. M. Shah, T. Chui, P. M. Garcia, J. G. Lee, R. C. Gentile, Y.-S. Hsiao, Q. Zhou, T. Ko, and R. Richard B., “Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients,” Retina 35(11), 2353–2363 (2015).
[Crossref]

Am. J. Ophthalmol. (2)

A. Ishibazawa, T. Nagaoka, A. Takahashi, T. Omae, T. Tani, K. Sogawa, H. Yokota, and A. Yoshida, “Optical coherence tomography angiography in diabetic retinopathy: a prospective pilot study,” Am. J. Ophthalmol. 160(1), 35–44.e1 (2015).
[Crossref]

D. Y. Lin, M. S. Blumenkranz, R. J. Brothers, D. M. Grosvenor, and T. D. D. S. Group, “The sensitivity and specificity of single-field nonmydriatic monochromatic digital fundus photography with remote image interpretation for diabetic retinopathy screening: a comparison with ophthalmoscopy and standardized mydriatic color photography,” Am. J. Ophthalmol. 134(2), 204–213 (2002).
[Crossref]

Arch. Ophthalmol. (1)

R. Klein, B. E. Klein, S. E. Moss, M. D. Davis, and D. L. DeMets, “The wisconsin epidemiologic study of diabetic retinopathy: Ii. prevalence and risk of diabetic retinopathy when age at diagnosis is less than 30 years,” Arch. Ophthalmol. 102(4), 520–526 (1984).
[Crossref]

Biomed. Opt. Express (8)

M. F. Kraus, B. Potsaid, M. A. Mayer, R. Bock, B. Baumann, J. J. Liu, J. Hornegger, and J. G. Fujimoto, “Motion correction in optical coherence tomography volumes on a per a-scan basis using orthogonal scan patterns,” Biomed. Opt. Express 3(6), 1182–1199 (2012).
[Crossref]

L. Liu, S. S. Gao, S. T. Bailey, D. Huang, D. Li, and Y. Jia, “Automated choroidal neovascularization detection algorithm for optical coherence tomography angiography,” Biomed. Opt. Express 6(9), 3564–3576 (2015).
[Crossref]

M. Zhang, J. Wang, A. D. Pechauer, T. S. Hwang, S. S. Gao, L. Liu, L. Liu, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Advanced image processing for optical coherence tomographic angiography of macular diseases,” Biomed. Opt. Express 6(12), 4661–4675 (2015).
[Crossref]

M. Zhang, T. S. Hwang, J. P. Campbell, S. T. Bailey, D. J. Wilson, D. Huang, and Y. Jia, “Projection-resolved optical coherence tomographic angiography,” Biomed. Opt. Express 7(3), 816–828 (2016).
[Crossref]

J. Wang, M. Zhang, T. S. Hwang, S. T. Bailey, D. Huang, D. J. Wilson, and Y. Jia, “Reflectance-based projection-resolved optical coherence tomography angiography,” Biomed. Opt. Express 8(3), 1536–1548 (2017).
[Crossref]

Y. Guo, A. Camino, M. Zhang, J. Wang, D. Huang, T. Hwang, and Y. Jia, “Automated segmentation of retinal layer boundaries and capillary plexuses in wide-field optical coherence tomographic angiography,” Biomed. Opt. Express 9(9), 4429–4442 (2018).
[Crossref]

Y. Guo, A. Camino, J. Wang, D. Huang, T. S. Hwang, and Y. Jia, “Mednet, a neural network for automated detection of avascular area in oct angiography,” Biomed. Opt. Express 9(11), 5147–5158 (2018).
[Crossref]

Y. Guo, T. T. Hormel, H. Xiong, B. Wang, A. Camino, J. Wang, D. Huang, T. S. Hwang, and Y. Jia, “Development and validation of a deep learning algorithm for distinguishing the nonperfusion area from signal reduction artifacts on oct angiography,” Biomed. Opt. Express 10(7), 3257–3268 (2019).
[Crossref]

BMC Ophthalmol. (1)

C. Shen, S. Yan, M. Du, H. Zhao, L. Shao, and Y. Hu, “Assessment of capillary dropout in the superficial retinal capillary plexus by optical coherence tomography angiography in the early stage of diabetic retinopathy,” BMC Ophthalmol. 18(1), 113 (2018).
[Crossref]

Br. J. Ophthalmol. (1)

M. M. Wessel, N. Nair, G. D. Aaker, J. R. Ehrlich, D. J. D’Amico, and S. Kiss, “Peripheral retinal ischaemia, as evaluated by ultra-widefield fluorescein angiography, is associated with diabetic macular oedema,” Br. J. Ophthalmol. 96(5), 694–698 (2012).
[Crossref]

Invest. Ophthalmol. Visual Sci. (5)

M. Zhang, T. S. Hwang, C. Dongye, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion in three retinal plexuses using projection-resolved optical coherence tomography angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 57(13), 5101–5106 (2016).
[Crossref]

D. A. Sim, P. A. Keane, S. Fung, M. Karampelas, S. R. Sadda, M. Fruttiger, P. J. Patel, A. Tufail, and C. A. Egan, “Quantitative analysis of diabetic macular ischemia using optical coherence tomography,” Invest. Ophthalmol. Visual Sci. 55(1), 417–423 (2014).
[Crossref]

P. L. Nesper, P. K. Roberts, A. C. Onishi, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Quantifying microvascular abnormalities with increasing severity of diabetic retinopathy using optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 58(6), BIO307 (2017).
[Crossref]

A. C. Onishi, P. L. Nesper, P. K. Roberts, G. A. Moharram, H. Chai, L. Liu, L. M. Jampol, and A. A. Fawzi, “Importance of considering the middle capillary plexus on oct angiography in diabetic retinopathy,” Invest. Ophthalmol. Visual Sci. 59(5), 2167–2176 (2018).
[Crossref]

K. Morino, T. Murakami, Y. Dodo, S. Yasukura, T. Yoshitake, M. Fujimoto, and A. Tsujikawa, “Characteristics of diabetic capillary nonperfusion in macular and extramacular white spots on optical coherence tomography angiography,” Invest. Ophthalmol. Visual Sci. 60(5), 1595–1603 (2019).
[Crossref]

JAMA Ophthalmol. (3)

T. S. Hwang, M. Zhang, K. Bhavsar, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. K. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Visualization of 3 distinct retinal plexuses by projection-resolved optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
[Crossref]

T. S. Hwang, A. M. Hagag, J. Wang, M. Zhang, A. Smith, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of nonperfusion areas in 3 vascular plexuses with optical coherence tomography angiography in eyes of patients with diabetes,” JAMA Ophthalmol. 136(8), 929–936 (2018).
[Crossref]

T. S. Hwang, S. S. Gao, L. Liu, A. K. Lauer, S. T. Bailey, C. J. Flaxel, D. J. Wilson, D. Huang, and Y. Jia, “Automated quantification of capillary nonperfusion using optical coherence tomography angiography in diabetic retinopathy,” JAMA Ophthalmol. 134(4), 367–373 (2016).
[Crossref]

Ophthalmic Surgery, Lasers Imaging Retin. (1)

J. J. Park, C. S. Chung, and A. A. Fawzi, “Visualizing structure and vascular interactions: macular nonperfusion in three capillary plexuses,” Ophthalmic Surgery, Lasers Imaging Retin. 49(11), e182–e190 (2018).
[Crossref]

Ophthalmol. Retin. (2)

J. J. Yu, A. Camino, L. Liu, X. Zhang, J. Wang, S. S. Gao, Y. Jia, and D. Huang, “Signal strength reduction effects in oct angiography,” Ophthalmol. Retin. 3(10), 835–842 (2019).
[Crossref]

R. C. Patel, J. Wang, T. S. Hwang, M. Zhang, S. S. Gao, M. E. Pennesi, S. T. Bailey, B. J. Lujan, X. Wang, D. J. Wilson, D. Huang, and Y. Jia, “Plexus-specific detection of retinal vascular pathologic conditions with projection-resolved oct angiography,” Ophthalmol. Retin. 2(8), 816–826 (2018).
[Crossref]

Ophthalmology (3)

K. Sakata, H. Funatsu, S. Harino, H. Noma, and S. Hori, “Relationship between macular microcirculation and progression of diabetic macular edema,” Ophthalmology 113(8), 1385–1391 (2006).
[Crossref]

Early Treatment Diabetic Retinopathy Study Research Group, “Fluorescein angiographic risk factors for progression of diabetic retinopathy: ETDRS report number 13,” Ophthalmology 98(5), 834–840 (1991).
[Crossref]

Diabetic Retinopathy Clinical Research Network, “Relationship between optical coherence tomography–measured central retinal thickness and visual acuity in diabetic macular edema,” Ophthalmology 114(3), 525–536 (2007).
[Crossref]

Opt. Express (1)

Proc. Natl. Acad. Sci. (1)

Y. Jia, S. T. Bailey, T. S. Hwang, S. M. McClintic, S. S. Gao, M. E. Pennesi, C. J. Flaxel, A. K. Lauer, D. J. Wilson, J. Hornegger, J. G. Fujimoto, and D. Huang, “Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye,” Proc. Natl. Acad. Sci. 112(18), E2395–E2402 (2015).
[Crossref]

Retina (3)

T. S. Hwang, Y. Jia, S. S. Gao, S. T. Bailey, A. K. Lauer, C. J. Flaxel, D. J. Wilson, and D. Huang, “Optical coherence tomography angiography features of diabetic retinopathy,” Retina 35(11), 2371–2376 (2015).
[Crossref]

J. Schottenhamml, E. M. Moult, S. Ploner, B. Lee, E. A. Novais, E. Cole, S. Dang, C. D. Lu, L. Husvogt, N. K. Waheed, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “An automatic intercapillary area based algorithm for quantifying diabetes related capillary dropout using oct angiography,” Retina 36, S93–S101 (2016).
[Crossref]

S. A. Agemy, N. K. Scripsema, C. M. Shah, T. Chui, P. M. Garcia, J. G. Lee, R. C. Gentile, Y.-S. Hsiao, Q. Zhou, T. Ko, and R. Richard B., “Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients,” Retina 35(11), 2353–2363 (2015).
[Crossref]

Sci. Rep. (1)

J. Campbell, M. Zhang, T. Hwang, S. Bailey, D. Wilson, Y. Jia, and D. Huang, “Detailed vascular anatomy of the human retina by projection-resolved optical coherence tomography angiography,” Sci. Rep. 7(1), 42201 (2017).
[Crossref]

Other (1)

A. Y. Alibhai, L. R. De Pretto, E. M. Moult, C. Or, M. Arya, M. McGowan, O. Carrasco-Zevallos, B. Lee, S. Chen, C. R. Baumal, A. J. Witkin, E. Reichel, A. Z. de Freitas, J. S. Duker, J. G. Fujimoto, and N. K. Waheed, “Quantification of retinal capillary nonperfusion in diabetics using wide-field optical coherence tomography angiography,” Retina (2018).

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Figures (15)

Fig. 1.
Fig. 1. Projection-resolved angiograms (bottom row) compared to original OCTA images (top row). (A), Cross-sectional structural OCT scans, with inner retinal flow signal overlaid in violet and choriocappilaris flow in red. Remaining columns are en face projections of (B), superficial vascular complex (SVC, inner $80\%$ of the ganglion cell complex); (C), intermediate capillary plexus (ICP,outer $20\%$ of the GCC and inner $50\%$ of the inner nuclear layer); (D), deep capillary plexus (DCP, outer $50\%$ of the INL and outer plexiform layer).
Fig. 2.
Fig. 2. Atrous kernels with rate = 1, 2 and 3. The red square is the center of kernel.
Fig. 3.
Fig. 3. CNN architecture for NPA detection. The numbers below each convolution block is the number of kernels for each convolution layer, atrous dilation rate was demonstrated below
Fig. 4.
Fig. 4. Ground truth generation. (A), In-house graphical user interface software; (B), manually graded NPA overlaid on the superficial vascular complex angiogram; (C), ground truth segmentation determined by majority vote from the three manually segmented images in (B).
Fig. 5.
Fig. 5. Manufactured signal strength attenuation on inner retina angiograms. (A), Uninhibited scan; (B), scan captured with a 0.6 neutral density filter; (C), scan captured with 4 diopters of defocus. SSI: Signal strength index.
Fig. 6.
Fig. 6. Effects of signal attenuation for NPA detection. (A), Normalized SSI (see text) declines as optical density of the neutral density filter increases; algorithm performance in the SVC (B), ICP (C), and DCP (D) is unaffected by increasing optical density, as evidenced by the low regression values and slopes of the best fit lines to the normalized FAZ areas (see text).
Fig. 7.
Fig. 7. Detected NPA (in blue) on optically filtered scans of a representative normal eye. The size and shape of the detected NPA (here, limited to the foveal avascular zone; FAZ) did not appreciably change with increasing optical density (columns running left to right).
Fig. 8.
Fig. 8. Effects of signal attenuation for NPA detection. (A), Normalized SSI (see text) declines as optical density of the neutral density filter increases; algorithm performance in the SVC (B), ICP (C), and DCP (D) is unaffected by increasing optical density, as evidenced by the low regression values and slopes of the best fit lines to normalized FAZ areas (see text).
Fig. 9.
Fig. 9. Detected NPA (in blue) on defocused scans of a representative normal eye. The size and shape of the detected NPA (here, limited to the foveal avascular zone; FAZ) did not appreciably change with increasing defocus (columns running left to right).
Fig. 10.
Fig. 10. Effects of SSI attenuation for NPA detection in three plexuses. NPA detection on the SVC (A), ICP (B) and DCP (C) were unaffected by SSI variation.
Fig. 11.
Fig. 11. Detected NPA (in blue) on a low-quality scan of non-proliferative DR affected by shadow artifacts (white arrows).
Fig. 12.
Fig. 12. Detected NPA (in blue) on a low-quality scan of proliferative DR eye affected by microsaccade artifacts.
Fig. 13.
Fig. 13. Detected NPA (in blue) on a low-quality scan of proliferative DR affected by bulk motion artifacts.
Fig. 14.
Fig. 14. NPA detection on a severe DR. (A), Angiograms in specific layers-superficial vascular complex (SVC), intermediate capillary plexus (ICP), and deep capillary plexus (DCP); (B), the ground truth delineated by an expert grader (green); (C), the output probabilities with brighter blue indicating a higher output probability; (D), the detected NPA (final results, with probability value $>0.5$ ).
Fig. 15.
Fig. 15. NPA detection on a healthy eye (in blue) affected by focal shadow artifacts (white arrows).

Tables (2)

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Table 1. Agreement between detected NPA and ground truth ( m e a n ± s t a n d a r d d e v i a t i o n ) grouped by DR severity

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Table 2. Repeatability of NPA detection on healthy eyes

Equations (5)

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J L 2 = i = 1 N y i l o g ( p i ) + α w T w
I O U = G T O u t G T O u t
p r e c i s i o n = T P T P + F P
r e c a l l = T P T P + F N
F 1 = 2 × p r e c i s i o n × r e c a l l p r e c i s i o n + r e c a l l

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