Abstract

Image-based angiography is a well-adapted technique to characterize vasculature, and has been used in retinal neurovascular studies. Because the microvasculature is of particular interest, being the site of exchange between blood and tissue, a high spatio-temporal resolution is required, implying the use of adaptive optics ophthalmoscopes with a high frame rate. Creating the opportunity for decoupled stimulation and imaging of the retina makes the use of near infrared (NIR) imaging light desirable, while the need for a large field of view and a lack of distortion implies the use of a flood illumination-based setup. However, flood-illumination NIR video sequences of erythrocytes, or red blood cells (RBC), have a limited contrast compared to scanning systems and visible light. As a result, they cannot be processed via existing image-based angiography methods. We have therefore developed a new computational method relying on a spatio-temporal filtering of the sequence to isolate blood flow from noise in low-contrast sequences. Applying this computational approach enabled us to perform angiography with an adaptive optics flood illumination ophthalmoscope (AO-FIO) using NIR light, both in bright-field and dark-field modalities. Finally, we demonstrate the capabilities of our system to differentiate blood flow velocity on a retinal capillary network in vivo.

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

Full Article  |  PDF Article
OSA Recommended Articles
High loop rate adaptive optics flood illumination ophthalmoscope with structured illumination capability

Elena Gofas-Salas, Pedro Mecê, Cyril Petit, Jessica Jarosz, Laurent M. Mugnier, Aurélie Montmerle Bonnefois, Kate Grieve, José Sahel, Michel Paques, and Serge Meimon
Appl. Opt. 57(20) 5635-5642 (2018)

Adaptive optics flood-illumination camera for high speed retinal imaging

Jungtae Rha, Ravi S. Jonnal, Karen E. Thorn, Junle Qu, Yan Zhang, and Donald T. Miller
Opt. Express 14(10) 4552-4569 (2006)

Noninvasive in vivo characterization of erythrocyte motion in human retinal capillaries using high-speed adaptive optics near-confocal imaging

Boyu Gu, Xiaolin Wang, Michael D. Twa, Johnny Tam, Christopher A. Girkin, and Yuhua Zhang
Biomed. Opt. Express 9(8) 3653-3677 (2018)

References

  • View by:
  • |
  • |
  • |

  1. T. Bek, “Regional morphology and pathophysiology of retinal vascular disease,” Prog. Retin. Eye Res. 36, 247–259 (2013).
    [Crossref] [PubMed]
  2. G. Michelson, J. Welzenbach, I. Pal, and J. Harazny, “Automatic full field analysis of perfusion images gained by scanning laser doppler flowmetry,” Br. J. Ophthalmol. 82, 1294–1300 (1998).
    [Crossref]
  3. R. D. Ferguson, D. X. Hammer, A. E. Elsner, R. H. Webb, S. A. Burns, and J. J. Weiter, “Wide-field retinal hemodynamic imaging with the tracking scanning laser ophthalmoscope,” Opt. Express 12, 5198–5208 (2004).
    [Crossref]
  4. T. Y. Chui, S. Mo, B. Krawitz, N. R. Menon, N. Choudhury, A. Gan, M. Razeen, N. Shah, A. Pinhas, and R. B. Rosen, “Human retinal microvascular imaging using adaptive optics scanning light ophthalmoscopy,” Int. J. Retin. Vitreous 2, 11 (2016).
    [Crossref]
  5. P. Bedggood and A. Metha, “Direct visualization and characterization of erythrocyte flow in human retinal capillaries,” Biomed. Opt. Express 3, 3264–3277 (2012).
    [Crossref] [PubMed]
  6. Z. Mammo, C. Balaratnasingam, P. Yu, J. Xu, M. Heisler, P. Mackenzie, A. Merkur, A. Kirker, D. Albiani, K. B. Freund, M. V. Sarunic, and D.-Y. Yu, “Quantitative noninvasive angiography of the fovea centralis using speckle variance optical coherence tomography,” Investig. Ophthalmol. & Vis. Sci. 56, 5074 (2015).
    [Crossref]
  7. R. F. Spaide, J. M. Klancnik, and M. J. Cooney, “Retinal vascular layers imaged by fluorescein angiography and optical coherence tomography angiography,” JAMA Ophthalmol. 133, 45–50 (2015).
    [Crossref]
  8. Y. Jia, J. C. Morrison, J. Tokayer, O. Tan, L. Lombardi, B. Baumann, C. D. Lu, W. Choi, J. G. Fujimoto, and D. Huang, “Quantitative oct angiography of optic nerve head blood flow,” Biomed. Opt. Express 3, 3127–3137 (2012).
    [Crossref]
  9. 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, 367–373 (2016).
    [Crossref]
  10. A. M. Hagag, S. S. Gao, Y. Jia, and D. Huang, “Optical coherence tomography angiography: technical principles and clinical applications in ophthalmology,” Taiwan J. Ophthalmol. 7, 115 (2017).
    [Crossref]
  11. J. Liang, D. R. Williams, and D. T. Miller, “Supernormal vision and high-resolution retinal imaging through adaptive optics,” JOSA A 14, 2884–2892 (1997).
    [Crossref]
  12. T. Y. Chui, Z. Zhong, H. Song, and S. A. Burns, “Foveal avascular zone and its relationship to foveal pit shape,” Optom. Vis. Sci. 89, 602 (2012).
    [Crossref]
  13. J. Tam and A. Roorda, “Speed quantification and tracking of moving objects in adaptive optics scanning laser ophthalmoscopy,” J. Biomed. Opt. 16, 036002 (2011).
    [Crossref]
  14. T. Y. Chui, D. A. VanNasdale, and S. A. Burns, “The use of forward scatter to improve retinal vascular imaging with an adaptive optics scanning laser ophthalmoscope,” Biomed. Opt. Express 3, 2537–2549 (2012).
    [Crossref]
  15. A. E. Salmon, R. F. Cooper, C. S. Langlo, A. Baghaie, A. Dubra, and J. Carroll, “An automated reference frame selection (arfs) algorithm for cone imaging with adaptive optics scanning light ophthalmoscopy,” Transl. Vis. Sci. & Technol. 6, 9(2017).
    [Crossref]
  16. A. de Castro, G. Huang, L. Sawides, T. Luo, and S. A. Burns, “Rapid high resolution imaging with a dual-channel scanning technique,” Opt. Lett. 41, 1881–1884 (2016).
    [Crossref]
  17. B. Gu, X. Wang, M. D. Twa, J. Tam, C. A. Girkin, and Y. Zhang, “Noninvasive in vivo characterization of erythrocyte motion in human retinal capillaries using high-speed adaptive optics near-confocal imaging,” Biomed. Opt. Express 9, 3653–3677 (2018).
    [Crossref]
  18. Z. Zhong, B. L. Petrig, X. Qi, and S. A. Burns, “In vivo measurement of erythrocyte velocity and retinal blood flow using adaptive optics scanning laser ophthalmoscopy,” Opt. Express 16, 12746–12756 (2008).
    [Crossref]
  19. P. Bedggood and A. Metha, “Analysis of contrast and motion signals generated by human blood constituents in capillary flow,” Opt. Lett. 39, 610–613 (2014).
    [Crossref]
  20. E. Gofas-Salas, P. Mecê, C. Petit, J. Jarosz, L. M. Mugnier, A. M. Bonnefois, K. Grieve, J. Sahel, M. Paques, and S. Meimon, “High loop rate adaptive optics flood illumination ophthalmoscope with structured illumination capability,” Appl. Opt. 57, 5635–5642 (2018).
    [Crossref]
  21. J. Lu, B. Gu, X. Wang, and Y. Zhang, “High-speed adaptive optics line scan confocal retinal imaging for human eye,” PloS one 12, e0169358 (2017).
    [Crossref] [PubMed]
  22. S. Meimon, E. G. Salas, P. Mecê, K. Grieve, J. A. Sahel, and M. Paques, “Manipulation of the illumination geometry on adaptive optics (ao) flood illumination ophthalmoscope (fio) for dark field imaging of the retina,” Investig. Ophthalmol. & Vis. Sci. 59, 4641 (2018).
  23. G. Ramaswamy and N. Devaney, “Pre-processing, registration and selection of adaptive optics corrected retinal images,” Ophthalmic Physiol. Opt. 33, 527–539 (2013).
    [Crossref]
  24. D. Gratadour, L. Mugnier, and D. Rouan, “Sub-pixel image registration with a maximum likelihood estimator-application to the first adaptive optics observations of arp 220 in the L’ band,” Astron. & Astrophys. 443, 357–365 (2005).
    [Crossref]
  25. L. Tian and L. Waller, “Quantitative differential phase contrast imaging in an led array microscope,” Opt. Express 23, 11394–11403 (2015).
    [Crossref] [PubMed]
  26. E. Meixner and G. Michelson, “Measurement of retinal wall-to-lumen ratio by adaptive optics retinal camera: a clinical research,” Graefe’s Arch. for Clin. Exp. Ophthalmol. 253, 1985–1995 (2015).
    [Crossref]
  27. R. Skalak and P. Branemark, “Deformation of red blood cells in capillaries,” Science 164, 717–719 (1969).
    [Crossref]
  28. A. Guevara-Torres, A. Joseph, and J. Schallek, “Label free measurement of retinal blood cell flux, velocity, hematocrit and capillary width in the living mouse eye,” Biomed. Opt. Express 7, 4228–4249 (2016).
    [Crossref]
  29. P. Mecê, E. Gofas-Salas, C. Petit, K. Grieve, C. Chabrier, M. Paques, and S. Meimon, “High ao-loop rate improves axial resolution in ao ophthalmoscopes,” ARVO Imaging Eye Conf. (2018).
  30. A. Nakano, Y. Sugii, M. Minamiyama, and H. Niimi, “Measurement of red cell velocity in microvessels using particle image velocimetry (piv),” Clin. Hemorheol. Microcirc. 29, 445–455 (2003).

2018 (3)

2017 (3)

J. Lu, B. Gu, X. Wang, and Y. Zhang, “High-speed adaptive optics line scan confocal retinal imaging for human eye,” PloS one 12, e0169358 (2017).
[Crossref] [PubMed]

A. E. Salmon, R. F. Cooper, C. S. Langlo, A. Baghaie, A. Dubra, and J. Carroll, “An automated reference frame selection (arfs) algorithm for cone imaging with adaptive optics scanning light ophthalmoscopy,” Transl. Vis. Sci. & Technol. 6, 9(2017).
[Crossref]

A. M. Hagag, S. S. Gao, Y. Jia, and D. Huang, “Optical coherence tomography angiography: technical principles and clinical applications in ophthalmology,” Taiwan J. Ophthalmol. 7, 115 (2017).
[Crossref]

2016 (4)

A. de Castro, G. Huang, L. Sawides, T. Luo, and S. A. Burns, “Rapid high resolution imaging with a dual-channel scanning technique,” Opt. Lett. 41, 1881–1884 (2016).
[Crossref]

T. Y. Chui, S. Mo, B. Krawitz, N. R. Menon, N. Choudhury, A. Gan, M. Razeen, N. Shah, A. Pinhas, and R. B. Rosen, “Human retinal microvascular imaging using adaptive optics scanning light ophthalmoscopy,” Int. J. Retin. Vitreous 2, 11 (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, 367–373 (2016).
[Crossref]

A. Guevara-Torres, A. Joseph, and J. Schallek, “Label free measurement of retinal blood cell flux, velocity, hematocrit and capillary width in the living mouse eye,” Biomed. Opt. Express 7, 4228–4249 (2016).
[Crossref]

2015 (4)

L. Tian and L. Waller, “Quantitative differential phase contrast imaging in an led array microscope,” Opt. Express 23, 11394–11403 (2015).
[Crossref] [PubMed]

E. Meixner and G. Michelson, “Measurement of retinal wall-to-lumen ratio by adaptive optics retinal camera: a clinical research,” Graefe’s Arch. for Clin. Exp. Ophthalmol. 253, 1985–1995 (2015).
[Crossref]

Z. Mammo, C. Balaratnasingam, P. Yu, J. Xu, M. Heisler, P. Mackenzie, A. Merkur, A. Kirker, D. Albiani, K. B. Freund, M. V. Sarunic, and D.-Y. Yu, “Quantitative noninvasive angiography of the fovea centralis using speckle variance optical coherence tomography,” Investig. Ophthalmol. & Vis. Sci. 56, 5074 (2015).
[Crossref]

R. F. Spaide, J. M. Klancnik, and M. J. Cooney, “Retinal vascular layers imaged by fluorescein angiography and optical coherence tomography angiography,” JAMA Ophthalmol. 133, 45–50 (2015).
[Crossref]

2014 (1)

2013 (2)

G. Ramaswamy and N. Devaney, “Pre-processing, registration and selection of adaptive optics corrected retinal images,” Ophthalmic Physiol. Opt. 33, 527–539 (2013).
[Crossref]

T. Bek, “Regional morphology and pathophysiology of retinal vascular disease,” Prog. Retin. Eye Res. 36, 247–259 (2013).
[Crossref] [PubMed]

2012 (4)

2011 (1)

J. Tam and A. Roorda, “Speed quantification and tracking of moving objects in adaptive optics scanning laser ophthalmoscopy,” J. Biomed. Opt. 16, 036002 (2011).
[Crossref]

2008 (1)

2005 (1)

D. Gratadour, L. Mugnier, and D. Rouan, “Sub-pixel image registration with a maximum likelihood estimator-application to the first adaptive optics observations of arp 220 in the L’ band,” Astron. & Astrophys. 443, 357–365 (2005).
[Crossref]

2004 (1)

2003 (1)

A. Nakano, Y. Sugii, M. Minamiyama, and H. Niimi, “Measurement of red cell velocity in microvessels using particle image velocimetry (piv),” Clin. Hemorheol. Microcirc. 29, 445–455 (2003).

1998 (1)

G. Michelson, J. Welzenbach, I. Pal, and J. Harazny, “Automatic full field analysis of perfusion images gained by scanning laser doppler flowmetry,” Br. J. Ophthalmol. 82, 1294–1300 (1998).
[Crossref]

1997 (1)

J. Liang, D. R. Williams, and D. T. Miller, “Supernormal vision and high-resolution retinal imaging through adaptive optics,” JOSA A 14, 2884–2892 (1997).
[Crossref]

1969 (1)

R. Skalak and P. Branemark, “Deformation of red blood cells in capillaries,” Science 164, 717–719 (1969).
[Crossref]

Albiani, D.

Z. Mammo, C. Balaratnasingam, P. Yu, J. Xu, M. Heisler, P. Mackenzie, A. Merkur, A. Kirker, D. Albiani, K. B. Freund, M. V. Sarunic, and D.-Y. Yu, “Quantitative noninvasive angiography of the fovea centralis using speckle variance optical coherence tomography,” Investig. Ophthalmol. & Vis. Sci. 56, 5074 (2015).
[Crossref]

Baghaie, A.

A. E. Salmon, R. F. Cooper, C. S. Langlo, A. Baghaie, A. Dubra, and J. Carroll, “An automated reference frame selection (arfs) algorithm for cone imaging with adaptive optics scanning light ophthalmoscopy,” Transl. Vis. Sci. & Technol. 6, 9(2017).
[Crossref]

Bailey, S. T.

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, 367–373 (2016).
[Crossref]

Balaratnasingam, C.

Z. Mammo, C. Balaratnasingam, P. Yu, J. Xu, M. Heisler, P. Mackenzie, A. Merkur, A. Kirker, D. Albiani, K. B. Freund, M. V. Sarunic, and D.-Y. Yu, “Quantitative noninvasive angiography of the fovea centralis using speckle variance optical coherence tomography,” Investig. Ophthalmol. & Vis. Sci. 56, 5074 (2015).
[Crossref]

Baumann, B.

Bedggood, P.

Bek, T.

T. Bek, “Regional morphology and pathophysiology of retinal vascular disease,” Prog. Retin. Eye Res. 36, 247–259 (2013).
[Crossref] [PubMed]

Bonnefois, A. M.

Branemark, P.

R. Skalak and P. Branemark, “Deformation of red blood cells in capillaries,” Science 164, 717–719 (1969).
[Crossref]

Burns, S. A.

Carroll, J.

A. E. Salmon, R. F. Cooper, C. S. Langlo, A. Baghaie, A. Dubra, and J. Carroll, “An automated reference frame selection (arfs) algorithm for cone imaging with adaptive optics scanning light ophthalmoscopy,” Transl. Vis. Sci. & Technol. 6, 9(2017).
[Crossref]

Chabrier, C.

P. Mecê, E. Gofas-Salas, C. Petit, K. Grieve, C. Chabrier, M. Paques, and S. Meimon, “High ao-loop rate improves axial resolution in ao ophthalmoscopes,” ARVO Imaging Eye Conf. (2018).

Choi, W.

Choudhury, N.

T. Y. Chui, S. Mo, B. Krawitz, N. R. Menon, N. Choudhury, A. Gan, M. Razeen, N. Shah, A. Pinhas, and R. B. Rosen, “Human retinal microvascular imaging using adaptive optics scanning light ophthalmoscopy,” Int. J. Retin. Vitreous 2, 11 (2016).
[Crossref]

Chui, T. Y.

T. Y. Chui, S. Mo, B. Krawitz, N. R. Menon, N. Choudhury, A. Gan, M. Razeen, N. Shah, A. Pinhas, and R. B. Rosen, “Human retinal microvascular imaging using adaptive optics scanning light ophthalmoscopy,” Int. J. Retin. Vitreous 2, 11 (2016).
[Crossref]

T. Y. Chui, Z. Zhong, H. Song, and S. A. Burns, “Foveal avascular zone and its relationship to foveal pit shape,” Optom. Vis. Sci. 89, 602 (2012).
[Crossref]

T. Y. Chui, D. A. VanNasdale, and S. A. Burns, “The use of forward scatter to improve retinal vascular imaging with an adaptive optics scanning laser ophthalmoscope,” Biomed. Opt. Express 3, 2537–2549 (2012).
[Crossref]

Cooney, M. J.

R. F. Spaide, J. M. Klancnik, and M. J. Cooney, “Retinal vascular layers imaged by fluorescein angiography and optical coherence tomography angiography,” JAMA Ophthalmol. 133, 45–50 (2015).
[Crossref]

Cooper, R. F.

A. E. Salmon, R. F. Cooper, C. S. Langlo, A. Baghaie, A. Dubra, and J. Carroll, “An automated reference frame selection (arfs) algorithm for cone imaging with adaptive optics scanning light ophthalmoscopy,” Transl. Vis. Sci. & Technol. 6, 9(2017).
[Crossref]

de Castro, A.

Devaney, N.

G. Ramaswamy and N. Devaney, “Pre-processing, registration and selection of adaptive optics corrected retinal images,” Ophthalmic Physiol. Opt. 33, 527–539 (2013).
[Crossref]

Dubra, A.

A. E. Salmon, R. F. Cooper, C. S. Langlo, A. Baghaie, A. Dubra, and J. Carroll, “An automated reference frame selection (arfs) algorithm for cone imaging with adaptive optics scanning light ophthalmoscopy,” Transl. Vis. Sci. & Technol. 6, 9(2017).
[Crossref]

Elsner, A. E.

Ferguson, R. D.

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, 367–373 (2016).
[Crossref]

Freund, K. B.

Z. Mammo, C. Balaratnasingam, P. Yu, J. Xu, M. Heisler, P. Mackenzie, A. Merkur, A. Kirker, D. Albiani, K. B. Freund, M. V. Sarunic, and D.-Y. Yu, “Quantitative noninvasive angiography of the fovea centralis using speckle variance optical coherence tomography,” Investig. Ophthalmol. & Vis. Sci. 56, 5074 (2015).
[Crossref]

Fujimoto, J. G.

Gan, A.

T. Y. Chui, S. Mo, B. Krawitz, N. R. Menon, N. Choudhury, A. Gan, M. Razeen, N. Shah, A. Pinhas, and R. B. Rosen, “Human retinal microvascular imaging using adaptive optics scanning light ophthalmoscopy,” Int. J. Retin. Vitreous 2, 11 (2016).
[Crossref]

Gao, S. S.

A. M. Hagag, S. S. Gao, Y. Jia, and D. Huang, “Optical coherence tomography angiography: technical principles and clinical applications in ophthalmology,” Taiwan J. Ophthalmol. 7, 115 (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, 367–373 (2016).
[Crossref]

Girkin, C. A.

Gofas-Salas, E.

E. Gofas-Salas, P. Mecê, C. Petit, J. Jarosz, L. M. Mugnier, A. M. Bonnefois, K. Grieve, J. Sahel, M. Paques, and S. Meimon, “High loop rate adaptive optics flood illumination ophthalmoscope with structured illumination capability,” Appl. Opt. 57, 5635–5642 (2018).
[Crossref]

P. Mecê, E. Gofas-Salas, C. Petit, K. Grieve, C. Chabrier, M. Paques, and S. Meimon, “High ao-loop rate improves axial resolution in ao ophthalmoscopes,” ARVO Imaging Eye Conf. (2018).

Gratadour, D.

D. Gratadour, L. Mugnier, and D. Rouan, “Sub-pixel image registration with a maximum likelihood estimator-application to the first adaptive optics observations of arp 220 in the L’ band,” Astron. & Astrophys. 443, 357–365 (2005).
[Crossref]

Grieve, K.

E. Gofas-Salas, P. Mecê, C. Petit, J. Jarosz, L. M. Mugnier, A. M. Bonnefois, K. Grieve, J. Sahel, M. Paques, and S. Meimon, “High loop rate adaptive optics flood illumination ophthalmoscope with structured illumination capability,” Appl. Opt. 57, 5635–5642 (2018).
[Crossref]

S. Meimon, E. G. Salas, P. Mecê, K. Grieve, J. A. Sahel, and M. Paques, “Manipulation of the illumination geometry on adaptive optics (ao) flood illumination ophthalmoscope (fio) for dark field imaging of the retina,” Investig. Ophthalmol. & Vis. Sci. 59, 4641 (2018).

P. Mecê, E. Gofas-Salas, C. Petit, K. Grieve, C. Chabrier, M. Paques, and S. Meimon, “High ao-loop rate improves axial resolution in ao ophthalmoscopes,” ARVO Imaging Eye Conf. (2018).

Gu, B.

Guevara-Torres, A.

Hagag, A. M.

A. M. Hagag, S. S. Gao, Y. Jia, and D. Huang, “Optical coherence tomography angiography: technical principles and clinical applications in ophthalmology,” Taiwan J. Ophthalmol. 7, 115 (2017).
[Crossref]

Hammer, D. X.

Harazny, J.

G. Michelson, J. Welzenbach, I. Pal, and J. Harazny, “Automatic full field analysis of perfusion images gained by scanning laser doppler flowmetry,” Br. J. Ophthalmol. 82, 1294–1300 (1998).
[Crossref]

Heisler, M.

Z. Mammo, C. Balaratnasingam, P. Yu, J. Xu, M. Heisler, P. Mackenzie, A. Merkur, A. Kirker, D. Albiani, K. B. Freund, M. V. Sarunic, and D.-Y. Yu, “Quantitative noninvasive angiography of the fovea centralis using speckle variance optical coherence tomography,” Investig. Ophthalmol. & Vis. Sci. 56, 5074 (2015).
[Crossref]

Huang, D.

A. M. Hagag, S. S. Gao, Y. Jia, and D. Huang, “Optical coherence tomography angiography: technical principles and clinical applications in ophthalmology,” Taiwan J. Ophthalmol. 7, 115 (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, 367–373 (2016).
[Crossref]

Y. Jia, J. C. Morrison, J. Tokayer, O. Tan, L. Lombardi, B. Baumann, C. D. Lu, W. Choi, J. G. Fujimoto, and D. Huang, “Quantitative oct angiography of optic nerve head blood flow,” Biomed. Opt. Express 3, 3127–3137 (2012).
[Crossref]

Huang, G.

Hwang, T. S.

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, 367–373 (2016).
[Crossref]

Jarosz, J.

Jia, Y.

A. M. Hagag, S. S. Gao, Y. Jia, and D. Huang, “Optical coherence tomography angiography: technical principles and clinical applications in ophthalmology,” Taiwan J. Ophthalmol. 7, 115 (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, 367–373 (2016).
[Crossref]

Y. Jia, J. C. Morrison, J. Tokayer, O. Tan, L. Lombardi, B. Baumann, C. D. Lu, W. Choi, J. G. Fujimoto, and D. Huang, “Quantitative oct angiography of optic nerve head blood flow,” Biomed. Opt. Express 3, 3127–3137 (2012).
[Crossref]

Joseph, A.

Kirker, A.

Z. Mammo, C. Balaratnasingam, P. Yu, J. Xu, M. Heisler, P. Mackenzie, A. Merkur, A. Kirker, D. Albiani, K. B. Freund, M. V. Sarunic, and D.-Y. Yu, “Quantitative noninvasive angiography of the fovea centralis using speckle variance optical coherence tomography,” Investig. Ophthalmol. & Vis. Sci. 56, 5074 (2015).
[Crossref]

Klancnik, J. M.

R. F. Spaide, J. M. Klancnik, and M. J. Cooney, “Retinal vascular layers imaged by fluorescein angiography and optical coherence tomography angiography,” JAMA Ophthalmol. 133, 45–50 (2015).
[Crossref]

Krawitz, B.

T. Y. Chui, S. Mo, B. Krawitz, N. R. Menon, N. Choudhury, A. Gan, M. Razeen, N. Shah, A. Pinhas, and R. B. Rosen, “Human retinal microvascular imaging using adaptive optics scanning light ophthalmoscopy,” Int. J. Retin. Vitreous 2, 11 (2016).
[Crossref]

Langlo, C. S.

A. E. Salmon, R. F. Cooper, C. S. Langlo, A. Baghaie, A. Dubra, and J. Carroll, “An automated reference frame selection (arfs) algorithm for cone imaging with adaptive optics scanning light ophthalmoscopy,” Transl. Vis. Sci. & Technol. 6, 9(2017).
[Crossref]

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, 367–373 (2016).
[Crossref]

Liang, J.

J. Liang, D. R. Williams, and D. T. Miller, “Supernormal vision and high-resolution retinal imaging through adaptive optics,” JOSA A 14, 2884–2892 (1997).
[Crossref]

Liu, L.

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, 367–373 (2016).
[Crossref]

Lombardi, L.

Lu, C. D.

Lu, J.

J. Lu, B. Gu, X. Wang, and Y. Zhang, “High-speed adaptive optics line scan confocal retinal imaging for human eye,” PloS one 12, e0169358 (2017).
[Crossref] [PubMed]

Luo, T.

Mackenzie, P.

Z. Mammo, C. Balaratnasingam, P. Yu, J. Xu, M. Heisler, P. Mackenzie, A. Merkur, A. Kirker, D. Albiani, K. B. Freund, M. V. Sarunic, and D.-Y. Yu, “Quantitative noninvasive angiography of the fovea centralis using speckle variance optical coherence tomography,” Investig. Ophthalmol. & Vis. Sci. 56, 5074 (2015).
[Crossref]

Mammo, Z.

Z. Mammo, C. Balaratnasingam, P. Yu, J. Xu, M. Heisler, P. Mackenzie, A. Merkur, A. Kirker, D. Albiani, K. B. Freund, M. V. Sarunic, and D.-Y. Yu, “Quantitative noninvasive angiography of the fovea centralis using speckle variance optical coherence tomography,” Investig. Ophthalmol. & Vis. Sci. 56, 5074 (2015).
[Crossref]

Mecê, P.

S. Meimon, E. G. Salas, P. Mecê, K. Grieve, J. A. Sahel, and M. Paques, “Manipulation of the illumination geometry on adaptive optics (ao) flood illumination ophthalmoscope (fio) for dark field imaging of the retina,” Investig. Ophthalmol. & Vis. Sci. 59, 4641 (2018).

E. Gofas-Salas, P. Mecê, C. Petit, J. Jarosz, L. M. Mugnier, A. M. Bonnefois, K. Grieve, J. Sahel, M. Paques, and S. Meimon, “High loop rate adaptive optics flood illumination ophthalmoscope with structured illumination capability,” Appl. Opt. 57, 5635–5642 (2018).
[Crossref]

P. Mecê, E. Gofas-Salas, C. Petit, K. Grieve, C. Chabrier, M. Paques, and S. Meimon, “High ao-loop rate improves axial resolution in ao ophthalmoscopes,” ARVO Imaging Eye Conf. (2018).

Meimon, S.

E. Gofas-Salas, P. Mecê, C. Petit, J. Jarosz, L. M. Mugnier, A. M. Bonnefois, K. Grieve, J. Sahel, M. Paques, and S. Meimon, “High loop rate adaptive optics flood illumination ophthalmoscope with structured illumination capability,” Appl. Opt. 57, 5635–5642 (2018).
[Crossref]

S. Meimon, E. G. Salas, P. Mecê, K. Grieve, J. A. Sahel, and M. Paques, “Manipulation of the illumination geometry on adaptive optics (ao) flood illumination ophthalmoscope (fio) for dark field imaging of the retina,” Investig. Ophthalmol. & Vis. Sci. 59, 4641 (2018).

P. Mecê, E. Gofas-Salas, C. Petit, K. Grieve, C. Chabrier, M. Paques, and S. Meimon, “High ao-loop rate improves axial resolution in ao ophthalmoscopes,” ARVO Imaging Eye Conf. (2018).

Meixner, E.

E. Meixner and G. Michelson, “Measurement of retinal wall-to-lumen ratio by adaptive optics retinal camera: a clinical research,” Graefe’s Arch. for Clin. Exp. Ophthalmol. 253, 1985–1995 (2015).
[Crossref]

Menon, N. R.

T. Y. Chui, S. Mo, B. Krawitz, N. R. Menon, N. Choudhury, A. Gan, M. Razeen, N. Shah, A. Pinhas, and R. B. Rosen, “Human retinal microvascular imaging using adaptive optics scanning light ophthalmoscopy,” Int. J. Retin. Vitreous 2, 11 (2016).
[Crossref]

Merkur, A.

Z. Mammo, C. Balaratnasingam, P. Yu, J. Xu, M. Heisler, P. Mackenzie, A. Merkur, A. Kirker, D. Albiani, K. B. Freund, M. V. Sarunic, and D.-Y. Yu, “Quantitative noninvasive angiography of the fovea centralis using speckle variance optical coherence tomography,” Investig. Ophthalmol. & Vis. Sci. 56, 5074 (2015).
[Crossref]

Metha, A.

Michelson, G.

E. Meixner and G. Michelson, “Measurement of retinal wall-to-lumen ratio by adaptive optics retinal camera: a clinical research,” Graefe’s Arch. for Clin. Exp. Ophthalmol. 253, 1985–1995 (2015).
[Crossref]

G. Michelson, J. Welzenbach, I. Pal, and J. Harazny, “Automatic full field analysis of perfusion images gained by scanning laser doppler flowmetry,” Br. J. Ophthalmol. 82, 1294–1300 (1998).
[Crossref]

Miller, D. T.

J. Liang, D. R. Williams, and D. T. Miller, “Supernormal vision and high-resolution retinal imaging through adaptive optics,” JOSA A 14, 2884–2892 (1997).
[Crossref]

Minamiyama, M.

A. Nakano, Y. Sugii, M. Minamiyama, and H. Niimi, “Measurement of red cell velocity in microvessels using particle image velocimetry (piv),” Clin. Hemorheol. Microcirc. 29, 445–455 (2003).

Mo, S.

T. Y. Chui, S. Mo, B. Krawitz, N. R. Menon, N. Choudhury, A. Gan, M. Razeen, N. Shah, A. Pinhas, and R. B. Rosen, “Human retinal microvascular imaging using adaptive optics scanning light ophthalmoscopy,” Int. J. Retin. Vitreous 2, 11 (2016).
[Crossref]

Morrison, J. C.

Mugnier, L.

D. Gratadour, L. Mugnier, and D. Rouan, “Sub-pixel image registration with a maximum likelihood estimator-application to the first adaptive optics observations of arp 220 in the L’ band,” Astron. & Astrophys. 443, 357–365 (2005).
[Crossref]

Mugnier, L. M.

Nakano, A.

A. Nakano, Y. Sugii, M. Minamiyama, and H. Niimi, “Measurement of red cell velocity in microvessels using particle image velocimetry (piv),” Clin. Hemorheol. Microcirc. 29, 445–455 (2003).

Niimi, H.

A. Nakano, Y. Sugii, M. Minamiyama, and H. Niimi, “Measurement of red cell velocity in microvessels using particle image velocimetry (piv),” Clin. Hemorheol. Microcirc. 29, 445–455 (2003).

Pal, I.

G. Michelson, J. Welzenbach, I. Pal, and J. Harazny, “Automatic full field analysis of perfusion images gained by scanning laser doppler flowmetry,” Br. J. Ophthalmol. 82, 1294–1300 (1998).
[Crossref]

Paques, M.

S. Meimon, E. G. Salas, P. Mecê, K. Grieve, J. A. Sahel, and M. Paques, “Manipulation of the illumination geometry on adaptive optics (ao) flood illumination ophthalmoscope (fio) for dark field imaging of the retina,” Investig. Ophthalmol. & Vis. Sci. 59, 4641 (2018).

E. Gofas-Salas, P. Mecê, C. Petit, J. Jarosz, L. M. Mugnier, A. M. Bonnefois, K. Grieve, J. Sahel, M. Paques, and S. Meimon, “High loop rate adaptive optics flood illumination ophthalmoscope with structured illumination capability,” Appl. Opt. 57, 5635–5642 (2018).
[Crossref]

P. Mecê, E. Gofas-Salas, C. Petit, K. Grieve, C. Chabrier, M. Paques, and S. Meimon, “High ao-loop rate improves axial resolution in ao ophthalmoscopes,” ARVO Imaging Eye Conf. (2018).

Petit, C.

E. Gofas-Salas, P. Mecê, C. Petit, J. Jarosz, L. M. Mugnier, A. M. Bonnefois, K. Grieve, J. Sahel, M. Paques, and S. Meimon, “High loop rate adaptive optics flood illumination ophthalmoscope with structured illumination capability,” Appl. Opt. 57, 5635–5642 (2018).
[Crossref]

P. Mecê, E. Gofas-Salas, C. Petit, K. Grieve, C. Chabrier, M. Paques, and S. Meimon, “High ao-loop rate improves axial resolution in ao ophthalmoscopes,” ARVO Imaging Eye Conf. (2018).

Petrig, B. L.

Pinhas, A.

T. Y. Chui, S. Mo, B. Krawitz, N. R. Menon, N. Choudhury, A. Gan, M. Razeen, N. Shah, A. Pinhas, and R. B. Rosen, “Human retinal microvascular imaging using adaptive optics scanning light ophthalmoscopy,” Int. J. Retin. Vitreous 2, 11 (2016).
[Crossref]

Qi, X.

Ramaswamy, G.

G. Ramaswamy and N. Devaney, “Pre-processing, registration and selection of adaptive optics corrected retinal images,” Ophthalmic Physiol. Opt. 33, 527–539 (2013).
[Crossref]

Razeen, M.

T. Y. Chui, S. Mo, B. Krawitz, N. R. Menon, N. Choudhury, A. Gan, M. Razeen, N. Shah, A. Pinhas, and R. B. Rosen, “Human retinal microvascular imaging using adaptive optics scanning light ophthalmoscopy,” Int. J. Retin. Vitreous 2, 11 (2016).
[Crossref]

Roorda, A.

J. Tam and A. Roorda, “Speed quantification and tracking of moving objects in adaptive optics scanning laser ophthalmoscopy,” J. Biomed. Opt. 16, 036002 (2011).
[Crossref]

Rosen, R. B.

T. Y. Chui, S. Mo, B. Krawitz, N. R. Menon, N. Choudhury, A. Gan, M. Razeen, N. Shah, A. Pinhas, and R. B. Rosen, “Human retinal microvascular imaging using adaptive optics scanning light ophthalmoscopy,” Int. J. Retin. Vitreous 2, 11 (2016).
[Crossref]

Rouan, D.

D. Gratadour, L. Mugnier, and D. Rouan, “Sub-pixel image registration with a maximum likelihood estimator-application to the first adaptive optics observations of arp 220 in the L’ band,” Astron. & Astrophys. 443, 357–365 (2005).
[Crossref]

Sahel, J.

Sahel, J. A.

S. Meimon, E. G. Salas, P. Mecê, K. Grieve, J. A. Sahel, and M. Paques, “Manipulation of the illumination geometry on adaptive optics (ao) flood illumination ophthalmoscope (fio) for dark field imaging of the retina,” Investig. Ophthalmol. & Vis. Sci. 59, 4641 (2018).

Salas, E. G.

S. Meimon, E. G. Salas, P. Mecê, K. Grieve, J. A. Sahel, and M. Paques, “Manipulation of the illumination geometry on adaptive optics (ao) flood illumination ophthalmoscope (fio) for dark field imaging of the retina,” Investig. Ophthalmol. & Vis. Sci. 59, 4641 (2018).

Salmon, A. E.

A. E. Salmon, R. F. Cooper, C. S. Langlo, A. Baghaie, A. Dubra, and J. Carroll, “An automated reference frame selection (arfs) algorithm for cone imaging with adaptive optics scanning light ophthalmoscopy,” Transl. Vis. Sci. & Technol. 6, 9(2017).
[Crossref]

Sarunic, M. V.

Z. Mammo, C. Balaratnasingam, P. Yu, J. Xu, M. Heisler, P. Mackenzie, A. Merkur, A. Kirker, D. Albiani, K. B. Freund, M. V. Sarunic, and D.-Y. Yu, “Quantitative noninvasive angiography of the fovea centralis using speckle variance optical coherence tomography,” Investig. Ophthalmol. & Vis. Sci. 56, 5074 (2015).
[Crossref]

Sawides, L.

Schallek, J.

Shah, N.

T. Y. Chui, S. Mo, B. Krawitz, N. R. Menon, N. Choudhury, A. Gan, M. Razeen, N. Shah, A. Pinhas, and R. B. Rosen, “Human retinal microvascular imaging using adaptive optics scanning light ophthalmoscopy,” Int. J. Retin. Vitreous 2, 11 (2016).
[Crossref]

Skalak, R.

R. Skalak and P. Branemark, “Deformation of red blood cells in capillaries,” Science 164, 717–719 (1969).
[Crossref]

Song, H.

T. Y. Chui, Z. Zhong, H. Song, and S. A. Burns, “Foveal avascular zone and its relationship to foveal pit shape,” Optom. Vis. Sci. 89, 602 (2012).
[Crossref]

Spaide, R. F.

R. F. Spaide, J. M. Klancnik, and M. J. Cooney, “Retinal vascular layers imaged by fluorescein angiography and optical coherence tomography angiography,” JAMA Ophthalmol. 133, 45–50 (2015).
[Crossref]

Sugii, Y.

A. Nakano, Y. Sugii, M. Minamiyama, and H. Niimi, “Measurement of red cell velocity in microvessels using particle image velocimetry (piv),” Clin. Hemorheol. Microcirc. 29, 445–455 (2003).

Tam, J.

Tan, O.

Tian, L.

Tokayer, J.

Twa, M. D.

VanNasdale, D. A.

Waller, L.

Wang, X.

Webb, R. H.

Weiter, J. J.

Welzenbach, J.

G. Michelson, J. Welzenbach, I. Pal, and J. Harazny, “Automatic full field analysis of perfusion images gained by scanning laser doppler flowmetry,” Br. J. Ophthalmol. 82, 1294–1300 (1998).
[Crossref]

Williams, D. R.

J. Liang, D. R. Williams, and D. T. Miller, “Supernormal vision and high-resolution retinal imaging through adaptive optics,” JOSA A 14, 2884–2892 (1997).
[Crossref]

Wilson, D. 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, 367–373 (2016).
[Crossref]

Xu, J.

Z. Mammo, C. Balaratnasingam, P. Yu, J. Xu, M. Heisler, P. Mackenzie, A. Merkur, A. Kirker, D. Albiani, K. B. Freund, M. V. Sarunic, and D.-Y. Yu, “Quantitative noninvasive angiography of the fovea centralis using speckle variance optical coherence tomography,” Investig. Ophthalmol. & Vis. Sci. 56, 5074 (2015).
[Crossref]

Yu, D.-Y.

Z. Mammo, C. Balaratnasingam, P. Yu, J. Xu, M. Heisler, P. Mackenzie, A. Merkur, A. Kirker, D. Albiani, K. B. Freund, M. V. Sarunic, and D.-Y. Yu, “Quantitative noninvasive angiography of the fovea centralis using speckle variance optical coherence tomography,” Investig. Ophthalmol. & Vis. Sci. 56, 5074 (2015).
[Crossref]

Yu, P.

Z. Mammo, C. Balaratnasingam, P. Yu, J. Xu, M. Heisler, P. Mackenzie, A. Merkur, A. Kirker, D. Albiani, K. B. Freund, M. V. Sarunic, and D.-Y. Yu, “Quantitative noninvasive angiography of the fovea centralis using speckle variance optical coherence tomography,” Investig. Ophthalmol. & Vis. Sci. 56, 5074 (2015).
[Crossref]

Zhang, Y.

Zhong, Z.

Appl. Opt. (1)

Astron. & Astrophys. (1)

D. Gratadour, L. Mugnier, and D. Rouan, “Sub-pixel image registration with a maximum likelihood estimator-application to the first adaptive optics observations of arp 220 in the L’ band,” Astron. & Astrophys. 443, 357–365 (2005).
[Crossref]

Biomed. Opt. Express (5)

Br. J. Ophthalmol. (1)

G. Michelson, J. Welzenbach, I. Pal, and J. Harazny, “Automatic full field analysis of perfusion images gained by scanning laser doppler flowmetry,” Br. J. Ophthalmol. 82, 1294–1300 (1998).
[Crossref]

Clin. Hemorheol. Microcirc. (1)

A. Nakano, Y. Sugii, M. Minamiyama, and H. Niimi, “Measurement of red cell velocity in microvessels using particle image velocimetry (piv),” Clin. Hemorheol. Microcirc. 29, 445–455 (2003).

Graefe’s Arch. for Clin. Exp. Ophthalmol. (1)

E. Meixner and G. Michelson, “Measurement of retinal wall-to-lumen ratio by adaptive optics retinal camera: a clinical research,” Graefe’s Arch. for Clin. Exp. Ophthalmol. 253, 1985–1995 (2015).
[Crossref]

Int. J. Retin. Vitreous (1)

T. Y. Chui, S. Mo, B. Krawitz, N. R. Menon, N. Choudhury, A. Gan, M. Razeen, N. Shah, A. Pinhas, and R. B. Rosen, “Human retinal microvascular imaging using adaptive optics scanning light ophthalmoscopy,” Int. J. Retin. Vitreous 2, 11 (2016).
[Crossref]

Investig. Ophthalmol. & Vis. Sci. (2)

Z. Mammo, C. Balaratnasingam, P. Yu, J. Xu, M. Heisler, P. Mackenzie, A. Merkur, A. Kirker, D. Albiani, K. B. Freund, M. V. Sarunic, and D.-Y. Yu, “Quantitative noninvasive angiography of the fovea centralis using speckle variance optical coherence tomography,” Investig. Ophthalmol. & Vis. Sci. 56, 5074 (2015).
[Crossref]

S. Meimon, E. G. Salas, P. Mecê, K. Grieve, J. A. Sahel, and M. Paques, “Manipulation of the illumination geometry on adaptive optics (ao) flood illumination ophthalmoscope (fio) for dark field imaging of the retina,” Investig. Ophthalmol. & Vis. Sci. 59, 4641 (2018).

J. Biomed. Opt. (1)

J. Tam and A. Roorda, “Speed quantification and tracking of moving objects in adaptive optics scanning laser ophthalmoscopy,” J. Biomed. Opt. 16, 036002 (2011).
[Crossref]

JAMA Ophthalmol. (2)

R. F. Spaide, J. M. Klancnik, and M. J. Cooney, “Retinal vascular layers imaged by fluorescein angiography and optical coherence tomography angiography,” JAMA Ophthalmol. 133, 45–50 (2015).
[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, 367–373 (2016).
[Crossref]

JOSA A (1)

J. Liang, D. R. Williams, and D. T. Miller, “Supernormal vision and high-resolution retinal imaging through adaptive optics,” JOSA A 14, 2884–2892 (1997).
[Crossref]

Ophthalmic Physiol. Opt. (1)

G. Ramaswamy and N. Devaney, “Pre-processing, registration and selection of adaptive optics corrected retinal images,” Ophthalmic Physiol. Opt. 33, 527–539 (2013).
[Crossref]

Opt. Express (3)

Opt. Lett. (2)

Optom. Vis. Sci. (1)

T. Y. Chui, Z. Zhong, H. Song, and S. A. Burns, “Foveal avascular zone and its relationship to foveal pit shape,” Optom. Vis. Sci. 89, 602 (2012).
[Crossref]

PloS one (1)

J. Lu, B. Gu, X. Wang, and Y. Zhang, “High-speed adaptive optics line scan confocal retinal imaging for human eye,” PloS one 12, e0169358 (2017).
[Crossref] [PubMed]

Prog. Retin. Eye Res. (1)

T. Bek, “Regional morphology and pathophysiology of retinal vascular disease,” Prog. Retin. Eye Res. 36, 247–259 (2013).
[Crossref] [PubMed]

Science (1)

R. Skalak and P. Branemark, “Deformation of red blood cells in capillaries,” Science 164, 717–719 (1969).
[Crossref]

Taiwan J. Ophthalmol. (1)

A. M. Hagag, S. S. Gao, Y. Jia, and D. Huang, “Optical coherence tomography angiography: technical principles and clinical applications in ophthalmology,” Taiwan J. Ophthalmol. 7, 115 (2017).
[Crossref]

Transl. Vis. Sci. & Technol. (1)

A. E. Salmon, R. F. Cooper, C. S. Langlo, A. Baghaie, A. Dubra, and J. Carroll, “An automated reference frame selection (arfs) algorithm for cone imaging with adaptive optics scanning light ophthalmoscopy,” Transl. Vis. Sci. & Technol. 6, 9(2017).
[Crossref]

Other (1)

P. Mecê, E. Gofas-Salas, C. Petit, K. Grieve, C. Chabrier, M. Paques, and S. Meimon, “High ao-loop rate improves axial resolution in ao ophthalmoscopes,” ARVO Imaging Eye Conf. (2018).

Supplementary Material (7)

NameDescription
» Visualization 1       Image sequence showing an artery (top vessel) and vein (vessel on the bottom) laying on the nerve fiber layer of a healthy subject. Several branch venules are entering the vein. Acquisition frequency is 200Hz and visualization frequency is 50Hz. Scal
» Visualization 2       Same as Visualization 1, after spatio-temporal filtering. The clusters of red blood cells can be followed, especially during the first part of the video (diastole). Scale bar is 50µm.
» Visualization 3       Image sequence showing a peripheral retinal vessel laying on the nerve fiber layer of a healthy subject. Acquisition frequency is 200Hz and visualization frequency is 50Hz. Scale bar is 50µm. Image sequence was corrected of the inhomogenous backgroun
» Visualization 4       Image sequence showing a vessel laying on the nerve fiber layer of a healthy subject. The vessel is alternaltively illuminated in bright-field and dark-field configurations. The dark field in the center was generated using a field diaphragm in the il
» Visualization 5       Image sequence showing an artery near the lamina cribrosa of a healthy subject. Because of the dark-field configuration the various layers of the wall and the blood flow appear highly contrasted. Acquisition frequency is 200Hz and visualization frequ
» Visualization 6       Image sequence showing a bed of capillaries near the lamina cribrosa in a healthy subject.The red blood cells appear highly contrasted inside of capillaries on the top left side of the field of view. Acquisition frequency is 200Hz and visualization f
» Visualization 7       Concatenation of two image sequences showing the same region of an artery (vertical vessel) crossing a vein of a healthy subject in bright-field (left) and dark-field (right) respectively. Acquisition frequency is 200Hz and visualization frequency is

Cited By

OSA participates in Crossref's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (6)

Fig. 1
Fig. 1 Schematic drawing of the PARIS adaptive optics flood illumination ophthalmoscope. The system can be divided into two subsystems. Wavefront (WF) Sensing & Control, in yellow, is composed of a Reference Source (Ref Source), a Wavefront Sensor (WFS) (Micro-lens array, relay optics, and WFS camera), a WFS beacon source and a Deformable Mirror (DM). An additional calibration source can be inserted in place of the eye to calibrate the adaptive optics loop. The other subsystem, in purple, is Illumination & Detection and is composed of the retinal imaging camera and the corresponding wide field imaging source.
Fig. 2
Fig. 2 (A,C) Average images of peripheral retinal vessels on the nerve fiber layer bed.(B,D) Motion contrast maps of the same areas displayed on the average images (see Visualization 1, Visualization 2 and Visualization 3 in Supplementary data). (C,D) show both an artery and a vein. In (A,B) A magnified view (yellow box) on the nerve fiber bed shows how the capillaries, invisible in the average image (A), appear contrasted on the perfusion map (B). In (C,D) Longitudinal capillaries, indicated with red arrowheads, in black in the average image (C) appear as bright white spots on the perfusion map (D). A magnified view (yellow box) in (D) shows in detail the confluence of the vein with a venule. The large vessel display several parallel bright bands, with the central band being the brightest. Scale bars are 50 μm
Fig. 3
Fig. 3 (A,C) Average images including vessels with a contrast typical of dark-field modality and (B,D) their respective perfusion maps (see Visualization 4 and Visualization 5 in Supplementary data). (A) Large vessel of peripheral retina lying on the nerve fiber layer alternatively illuminated in bright-field and dark-field configuration. A magnified view (yellow box) in (B) shows the aspect of the perfusion map on a large vessel when illuminated in dark-field. The large vessel shows two parallel bands, with a darker aspect in the center of the vessel, instead of the typical several bands observed in bright-field configuration (cf. Fig 2(D)). Again, capillaries hardly visible in (A) appear contrasted in (B). (C) Artery from the optic nerve head region. The artery is lying over the lamina cribrosa which illuminates it from behind leading to forward scattering which gives this contrast to the vessel, characteristic of dark-field illumination. In (D) the large vessel lumen is easier to measure than in (C) where it is hard to determine the beginning of the wall (yellow lines). Scale bars are 50 μm
Fig. 4
Fig. 4 (A) Average image of a capillary bed near the lamina cribrosa region and (B) its respective perfusion map after a temporal filtering with a frequency bandwidth of [1Hz, 40Hz] (see Visualization 6 in Supplementary data). (C,D,E) Perfusion maps of that same region after three different temporal filtering, with respectively frequency bandwidths of [1Hz, 10Hz] (blue map), [10Hz, 25Hz] (green map) and [25Hz, 40Hz] (red map). (E) Perfusion color map generated by assigning to each perfusion map from a temporal frequency band (A,B,C) an RGB color. Slow temporal frequencies are in blue, medium in green and the faster frequencies corresponds to red. White arrowheads indicate two examples of longitudinal capillaries. Scale bars are 50 μm.
Fig. 5
Fig. 5 Images generated from image sequences of the same region showing an artery crossing with a vein in bright-field (A,B,C) and dark-field (D,F,E) illumination configuration respectively (see Visualization 7 in Supplementary data). (A,D) are average images, (B,E) perfusion maps and (C,F) color generated maps showing in green slow variations and in red fast variations. (G) displays two horizontal intensity profile plots (vertically averaged) from yellow boxes in images (B) and (E) corresponding to bright-field and dark-field perfusion maps respectively. The x-axis indicates the horizontal position in microns inside the yellow box and the y-axis indicates the brightness level of the vertical average for each of these horizontal positions.
Fig. 6
Fig. 6 Schematic drawings showing a cross-section of a vessel scattering light in bright-field (left) and dark-field (right). The red C letters represent red blood cells (or erythrocytes) and blue arrows represent light rays, dashed lines representing lower amount of photons while the solid lines show larger amounts.

Equations (1)

Equations on this page are rendered with MathJax. Learn more.

v RBC = 2 ϕ RBC ν