Reflectance-based projection-resolved optical coherence tomography angiography [Invited]

Jie Wang; Miao Zhang; Thomas S. Hwang; Steven T. Bailey; David Huang; David J. Wilson; Yali Jia

doi:10.1364/BOE.8.001536

Reflectance-based projection-resolved optical coherence tomography angiography [Invited]

Jie Wang, Miao Zhang, Thomas S. Hwang, Steven T. Bailey, David Huang, David J. Wilson, and Yali Jia

Biomedical Optics Express
Vol. 8,
Issue 3,
pp. 1536-1548
(2017)
•https://doi.org/10.1364/BOE.8.001536

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Jie Wang, Miao Zhang, Thomas S. Hwang, Steven T. Bailey, David Huang, David J. Wilson, and Yali Jia, "Reflectance-based projection-resolved optical coherence tomography angiography [Invited]," Biomed. Opt. Express 8, 1536-1548 (2017)

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Related Topics
Table of Contents Category
- Optical Coherence Tomography
Optics & Photonics Topics
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The topics in this list come from the OSA Optics and Photonics Topics applied to this article.
Previously assigned OCIS codes
- Image processing (100.0100)
- Image analysis (100.2960)
- Optical coherence tomography (110.4500)
- Ophthalmology (170.4470)

About this Article
History
- Original Manuscript: November 8, 2016
- Revised Manuscript: February 10, 2017
- Manuscript Accepted: February 10, 2017
- Published: February 15, 2017
Virtual Issues
Biomedical Optics Express 25 Year Anniversary of Optical Coherence Tomography (2017)

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Open Access

Abstract

Optical coherence tomography angiography (OCTA) is limited by projection artifacts from the superficial blood vessels onto deeper layers. We have recently described projection-resolved (PR) OCTA that solves the ambiguity between in situ flow and flow projection along each axial scan and suppresses the artifact on both en face and cross-sectional angiograms. While this method significantly improved the depth resolution of OCTA, the vascular integrity of the deeper layers was not fully preserved. In this study, we propose a novel reflectance-based projection-resolved (rbPR) OCTA algorithm which uses OCT reflectance to enhance the flow signal and suppress the projection artifacts in 3-dimensional OCTA. We demonstrated quantitatively that rbPR improved the vascular connectivity and improved the discrimination of the deeper plexus angiograms in healthy eyes, compared to prior PR-OCTA method. We also demonstrated qualitatively that rbPR removes flow projection artifacts more completely from the outer retinal slab in the eyes with age-related macular degeneration, and preserves vascular integrity of the intermediate and deep capillary plexuses in the eyes with diabetic retinopathy. Additionally, this method improves the resolution of the choriocapillaris and demonstrates details comparable to scanning electron microscopy.

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References

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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. U.S.A. 112(18), E2395–E2402 (2015).
[Crossref] [PubMed]
S. S. Gao, Y. Jia, M. Zhang, J. P. Su, G. Liu, T. S. Hwang, S. T. Bailey, and D. Huang, “Optical Coherence Tomography Angiography,” Invest. Ophthalmol. Vis. Sci. 57(9), OCT27–OCT36 (2016).
[Crossref] [PubMed]
D. Huang, Y. Jia, and S. S. Gao, “Principles of optical coherence tomography angiography,” in Clinical OCT Angiography Atlas(2015), p. 3.
R. F. Spaide, J. G. Fujimoto, and N. K. Waheed, “Image artifacts in optical coherence tomography angiography,” Retina 35(11), 2163–2180 (2015).
[Crossref] [PubMed]
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] [PubMed]
Y. Jia, S. T. Bailey, D. J. Wilson, O. Tan, M. L. Klein, C. J. Flaxel, B. Potsaid, J. J. Liu, C. D. Lu, M. F. Kraus, J. G. Fujimoto, and D. Huang, “Quantitative Optical Coherence Tomography Angiography of Choroidal Neovascularization in Age-Related Macular Degeneration,” Ophthalmology 121(7), 1435–1444 (2014).
[Crossref] [PubMed]
A. Zhang, Q. Zhang, and R. K. Wang, “Minimizing projection artifacts for accurate presentation of choroidal neovascularization in OCT micro-angiography,” Biomed. Opt. Express 6(10), 4130–4143 (2015).
[Crossref] [PubMed]
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] [PubMed]
G. Chan, C. Balaratnasingam, P. K. Yu, W. H. Morgan, I. L. McAllister, S. J. Cringle, and D.-Y. Yu, “Quantitative Morphometry of Perifoveal Capillary Networks in the Human Retina,” Invest. Ophthalmol. Vis. Sci. 53(9), 5502–5514 (2012).
[Crossref] [PubMed]
K. Singh and R. Kapoor, “Image enhancement using exposure based sub image histogram equalization,” Pattern Recognit. Lett. 36, 10–14 (2014).
[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] [PubMed]
L. Lam, S.-W. Lee, and C. Y. Suen, “Thinning methodologies-a comprehensive survey,” IEEE Trans. Pattern Anal. Mach. Intell. 14(9), 869–885 (1992).
[Crossref]
D. Huang, Y. Jia, M. Rispoli, O. Tan, and B. Lumbroso, “Optical coherence tomography angiography of time course of choroidal neovascularization in response to anti-angiogenic treatment,” Retina 35(11), 2260–2264 (2015).
[Crossref] [PubMed]
S. S. Gao, L. Liu, S. T. Bailey, C. J. Flaxel, D. Huang, D. Li, and Y. Jia, “Quantification of choroidal neovascularization vessel length using optical coherence tomography angiography,” J. Biomed. Opt. 21(7), 076010 (2016).
[Crossref] [PubMed]
S. M. McClintic, Y. Jia, D. Huang, and S. T. Bailey, “Optical coherence tomographic angiography of choroidal neovascularization associated with central serous chorioretinopathy,” JAMA Ophthalmol. 133(10), 1212–1214 (2015).
[Crossref] [PubMed]
T. S. Hwang, M. Zhang, K. Bhavsr, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Projection-resolved optical coherence tomography angiography visualizes capillary nonperfusion in three distinct retinal plexuses in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
[Crossref] [PubMed]
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. Vis. Sci. 57(13), 5101–5106 (2016).
[Crossref] [PubMed]
I. Bhutto and G. Lutty, “Understanding age-related macular degeneration (AMD): relationships between the photoreceptor/retinal pigment epithelium/Bruch’s membrane/choriocapillaris complex,” Mol. Aspects Med. 33(4), 295–317 (2012).
[Crossref] [PubMed]
G. A. Lutty, “Effects of Diabetes on the EyeEffects of Diabetes on the Eye,” Invest. Ophthalmol. Vis. Sci. 54(14), ORSF81–ORSF87 (2013).
J. M. Olver, “Functional anatomy of the choroidal circulation: methyl methacrylate casting of human choroid,” Eye (Lond.) 4(2), 262–272 (1990).
[Crossref] [PubMed]

2016 (5)

S. S. Gao, Y. Jia, M. Zhang, J. P. Su, G. Liu, T. S. Hwang, S. T. Bailey, and D. Huang, “Optical Coherence Tomography Angiography,” Invest. Ophthalmol. Vis. Sci. 57(9), OCT27–OCT36 (2016).
[Crossref] [PubMed]

S. S. Gao, L. Liu, S. T. Bailey, C. J. Flaxel, D. Huang, D. Li, and Y. Jia, “Quantification of choroidal neovascularization vessel length using optical coherence tomography angiography,” J. Biomed. Opt. 21(7), 076010 (2016).
[Crossref] [PubMed]

T. S. Hwang, M. Zhang, K. Bhavsr, X. Zhang, J. P. Campbell, P. Lin, S. T. Bailey, C. J. Flaxel, A. Lauer, D. J. Wilson, D. Huang, and Y. Jia, “Projection-resolved optical coherence tomography angiography visualizes capillary nonperfusion in three distinct retinal plexuses in diabetic retinopathy,” JAMA Ophthalmol. 134(12), 1411–1419 (2016).
[Crossref] [PubMed]

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. Vis. Sci. 57(13), 5101–5106 (2016).
[Crossref] [PubMed]

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] [PubMed]

2015 (7)

S. M. McClintic, Y. Jia, D. Huang, and S. T. Bailey, “Optical coherence tomographic angiography of choroidal neovascularization associated with central serous chorioretinopathy,” JAMA Ophthalmol. 133(10), 1212–1214 (2015).
[Crossref] [PubMed]

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] [PubMed]

A. Zhang, Q. Zhang, and R. K. Wang, “Minimizing projection artifacts for accurate presentation of choroidal neovascularization in OCT micro-angiography,” Biomed. Opt. Express 6(10), 4130–4143 (2015).
[Crossref] [PubMed]

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] [PubMed]

R. F. Spaide, J. G. Fujimoto, and N. K. Waheed, “Image artifacts in optical coherence tomography angiography,” Retina 35(11), 2163–2180 (2015).
[Crossref] [PubMed]

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. U.S.A. 112(18), E2395–E2402 (2015).
[Crossref] [PubMed]

D. Huang, Y. Jia, M. Rispoli, O. Tan, and B. Lumbroso, “Optical coherence tomography angiography of time course of choroidal neovascularization in response to anti-angiogenic treatment,” Retina 35(11), 2260–2264 (2015).
[Crossref] [PubMed]

2014 (2)

K. Singh and R. Kapoor, “Image enhancement using exposure based sub image histogram equalization,” Pattern Recognit. Lett. 36, 10–14 (2014).
[Crossref]

Y. Jia, S. T. Bailey, D. J. Wilson, O. Tan, M. L. Klein, C. J. Flaxel, B. Potsaid, J. J. Liu, C. D. Lu, M. F. Kraus, J. G. Fujimoto, and D. Huang, “Quantitative Optical Coherence Tomography Angiography of Choroidal Neovascularization in Age-Related Macular Degeneration,” Ophthalmology 121(7), 1435–1444 (2014).
[Crossref] [PubMed]

2013 (1)

G. A. Lutty, “Effects of Diabetes on the EyeEffects of Diabetes on the Eye,” Invest. Ophthalmol. Vis. Sci. 54(14), ORSF81–ORSF87 (2013).

2012 (2)

I. Bhutto and G. Lutty, “Understanding age-related macular degeneration (AMD): relationships between the photoreceptor/retinal pigment epithelium/Bruch’s membrane/choriocapillaris complex,” Mol. Aspects Med. 33(4), 295–317 (2012).
[Crossref] [PubMed]

G. Chan, C. Balaratnasingam, P. K. Yu, W. H. Morgan, I. L. McAllister, S. J. Cringle, and D.-Y. Yu, “Quantitative Morphometry of Perifoveal Capillary Networks in the Human Retina,” Invest. Ophthalmol. Vis. Sci. 53(9), 5502–5514 (2012).
[Crossref] [PubMed]

1992 (1)

L. Lam, S.-W. Lee, and C. Y. Suen, “Thinning methodologies-a comprehensive survey,” IEEE Trans. Pattern Anal. Mach. Intell. 14(9), 869–885 (1992).
[Crossref]

1990 (1)

J. M. Olver, “Functional anatomy of the choroidal circulation: methyl methacrylate casting of human choroid,” Eye (Lond.) 4(2), 262–272 (1990).
[Crossref] [PubMed]

Bailey, S. T.

Balaratnasingam, C.

Bhavsr, K.

Bhutto, I.

Campbell, J. P.

Chan, G.

Cringle, S. J.

Dongye, C.

Flaxel, C. J.

Fujimoto, J. G.

R. F. Spaide, J. G. Fujimoto, and N. K. Waheed, “Image artifacts in optical coherence tomography angiography,” Retina 35(11), 2163–2180 (2015).
[Crossref] [PubMed]

Gao, S. S.

Hornegger, J.

Huang, D.

Hwang, T. S.

Jia, Y.

Kapoor, R.

K. Singh and R. Kapoor, “Image enhancement using exposure based sub image histogram equalization,” Pattern Recognit. Lett. 36, 10–14 (2014).
[Crossref]

Klein, M. L.

Kraus, M. F.

Lam, L.

L. Lam, S.-W. Lee, and C. Y. Suen, “Thinning methodologies-a comprehensive survey,” IEEE Trans. Pattern Anal. Mach. Intell. 14(9), 869–885 (1992).
[Crossref]

Lauer, A.

Lauer, A. K.

Lee, S.-W.

L. Lam, S.-W. Lee, and C. Y. Suen, “Thinning methodologies-a comprehensive survey,” IEEE Trans. Pattern Anal. Mach. Intell. 14(9), 869–885 (1992).
[Crossref]

Li, D.

Lin, P.

Liu, G.

Liu, J. J.

Liu, L.

Lu, C. D.

Lumbroso, B.

Lutty, G.

Lutty, G. A.

G. A. Lutty, “Effects of Diabetes on the EyeEffects of Diabetes on the Eye,” Invest. Ophthalmol. Vis. Sci. 54(14), ORSF81–ORSF87 (2013).

McAllister, I. L.

McClintic, S. M.

Morgan, W. H.

Olver, J. M.

J. M. Olver, “Functional anatomy of the choroidal circulation: methyl methacrylate casting of human choroid,” Eye (Lond.) 4(2), 262–272 (1990).
[Crossref] [PubMed]

Pechauer, A. D.

Pennesi, M. E.

Potsaid, B.

Rispoli, M.

Singh, K.

K. Singh and R. Kapoor, “Image enhancement using exposure based sub image histogram equalization,” Pattern Recognit. Lett. 36, 10–14 (2014).
[Crossref]

Spaide, R. F.

R. F. Spaide, J. G. Fujimoto, and N. K. Waheed, “Image artifacts in optical coherence tomography angiography,” Retina 35(11), 2163–2180 (2015).
[Crossref] [PubMed]

Su, J. P.

Suen, C. Y.

L. Lam, S.-W. Lee, and C. Y. Suen, “Thinning methodologies-a comprehensive survey,” IEEE Trans. Pattern Anal. Mach. Intell. 14(9), 869–885 (1992).
[Crossref]

Tan, O.

Waheed, N. K.

R. F. Spaide, J. G. Fujimoto, and N. K. Waheed, “Image artifacts in optical coherence tomography angiography,” Retina 35(11), 2163–2180 (2015).
[Crossref] [PubMed]

Wang, J.

Wang, R. K.

Wilson, D. J.

Yu, D.-Y.

Yu, P. K.

Zhang, A.

Zhang, M.

Zhang, Q.

Zhang, X.

Biomed. Opt. Express (4)

Eye (Lond.) (1)

J. M. Olver, “Functional anatomy of the choroidal circulation: methyl methacrylate casting of human choroid,” Eye (Lond.) 4(2), 262–272 (1990).
[Crossref] [PubMed]

IEEE Trans. Pattern Anal. Mach. Intell. (1)

L. Lam, S.-W. Lee, and C. Y. Suen, “Thinning methodologies-a comprehensive survey,” IEEE Trans. Pattern Anal. Mach. Intell. 14(9), 869–885 (1992).
[Crossref]

Invest. Ophthalmol. Vis. Sci. (4)

G. A. Lutty, “Effects of Diabetes on the EyeEffects of Diabetes on the Eye,” Invest. Ophthalmol. Vis. Sci. 54(14), ORSF81–ORSF87 (2013).

J. Biomed. Opt. (1)

JAMA Ophthalmol. (2)

Mol. Aspects Med. (1)

Ophthalmology (1)

Pattern Recognit. Lett. (1)

K. Singh and R. Kapoor, “Image enhancement using exposure based sub image histogram equalization,” Pattern Recognit. Lett. 36, 10–14 (2014).
[Crossref]

Proc. Natl. Acad. Sci. U.S.A. (1)

Retina (2)

R. F. Spaide, J. G. Fujimoto, and N. K. Waheed, “Image artifacts in optical coherence tomography angiography,” Retina 35(11), 2163–2180 (2015).
[Crossref] [PubMed]

Other (1)

D. Huang, Y. Jia, and S. S. Gao, “Principles of optical coherence tomography angiography,” in Clinical OCT Angiography Atlas(2015), p. 3.

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Fig. 1 Illustration of the in situ blood flow and flow projection artifact on OCTA and their corresponding signal on structural OCT. (A) Cross-sectional structural OCT (gray) overlaid with OCTA (red). (B) The C-scan of OCT reflectance in deep plexus slab, indicated by yellow dotted line in A. (C1) and (C2) are magnified regions on B to show the vessel shadow artifacts with low reflectance (outlined by green) and the capillary network with high reflectance. (D) The C-scan of OCT reflectance in outer retinal slab, indicated by green dotted line in A. (E) The maximum projection of OCTA in superficial plexus slab, horizontal white dashed line indicates the location of panel A. (F) The C-scan of OCTA in deep plexus slab. (G1) and (G2) are magnified regions on F to show the real capillaries interfered by projection artifact (outline by green). (H) The C-scan of OCTA in outer retinal slab.

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Fig. 2 Overview of the reflectance-based projection-resolved (rbPR) OCTA algorithm. IS/OS: junction of inner and outer photoreceptor.

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Fig. 3 Illustration of A-line resize. (A) the original reflectance volume; (B) the volume showing resized A-scans above IS/OS . (C) the B-scan of panel A indicated with red arrow. (D) the B-scan of panel B indicated with blue arrow, which shows resized A-scan above IS/OS.

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Fig. 4 Illustration of reflectance distribution in whole scan volume (A), volume above photoreceptor inner/outer segment (IS/OS) (B) and volume below IS/OS (C). B₁ and B₂ are boundaries between low, medium and high reflectance. C_H is the center of high reflectance cluster.

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Fig. 5 Illustration of OCTA normalization using vessel contrast enhanced OCT reflectance at deep capillary plexus. (A) the C-scan of original OCT reflectance. (B) the vascular contrast enhanced C-scan. (C) the C-scan of original PR-OCTA. (D) the C-scan processed by normalizing C with B. As highlighted with white outlines, the projection artifacts were removed.

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Fig. 6 Vessel probability based vessel enhancement. (A) Projection suppressed C-scan OCTA processed by method described in section 3.3. (B) Vessel probability map calculated by the reflectance. (C) Vessel enhanced vascular image by multiplying A with B.

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Fig. 7 B-scan reflectance image overlaid with flow signal showing large vessel optimization in rbPR algorithm. (A) Original B-scan. (B) B-scan processed by rbPR without large vessel optimization. (C) B-scan processed by rbPR with large vessel optimization.

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Fig. 8 En face maximum projection of rbPR-OCTA in superficial vascular plexus (A), intermediate capillary plexus (B) and deep capillary plexus (C).

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Fig. 9 A comparison of retinal OCTA (3 × 3mm) from a normal participant processed without projection suppression (original, row 1), with projection suppressed by the prior projection-resolved method (PR, row 2) and the novel reflectance-based PR algorithm (rbPR, row 3). Column A: En face OCTA of the superficial vascular plexus. Column B: En face OCTA of the intermediate capillary plexus. Column C: En face OCTA of the deep capillary plexus. Column D: En face OCTA of the outer retinal slab. In A1, white circle (r0 = 0.3mm) and blue ring (r1 = 0.65mm, r2 = 1mm) mark the foveal avascular area and parafoveal annulus for the measurement of flow signal to noise ratio below.

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Fig. 10 A comparison of projection-resolved (PR) algorithms in the visualization of choroidal neovascularization (CNV) on both en face (3 × 3mm) and cross-sectional OCTA. (A1) and (A2) are En face and cross-sectional OCTA of the outer retinal slab without projection suppression, respectively. (B1) and (B2) are projection suppression with the prior PR algorithm. (C1) and (C2) are projection suppression with the proposed reflectance-based PR (rbPR) algorithm. The projection artifacts persistent on prior PR-OCTA were removed by rbPR (indicated by red arrows).

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Fig. 11 A comparison of retinal OCTA (6 × 6mm) processed without projection suppression (original, row 1), with projection suppressed by the prior projection-resolved method (PR, row 2) and the novel reflectance-based PR algorithm (rbPR, row 3). Column A: En face OCTA of the superficial vascular plexus. Column B: En face OCTA of the intermediate capillary plexus. Column C: En face OCTA of the deep capillary plexus. Column D: The magnified images in the positions indicated by a white box in C1.

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Fig. 12 A comparison of submacular choriocapillaries OCTA processed without projection suppression (column A), with projection suppressed by the prior projection-resolved method (PR, column B) and the novel reflectance-based PR algorithm (rbPR, column C). (A1-C1): En face OCTA of the choriocapillaries plexus. (A2-C2): The magnified images in the positions indicated by a white box in A1. (A3-C3): B-scan reflectance image overlaid with flow signal. (D) inner retinal angiogram. (E) chriocapillaris shown by scanning electron microscopy, reproduced from Olver et al.with permission [20]. The scale bar is 250 um.

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Tables (1)

Table 1 Comparison between prior PR and rbPR on quantitative matrics

View Table

Equations (7)

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

L S E_{1} = \sum_{k = 1}^{K} \sum_{L (i) = k} {‖ I (i) - C_{k} ‖}^{2}

{\begin{matrix} L (i) = k, \arg \min_{k} {‖ I (i) - C (k) ‖}^{2} \\ C (k) = \frac{\sum_{L (i) = k} I (i)}{\sum_{L (i) = k} 1} \end{matrix}

I_{e} (i) = {\begin{matrix} B_{1} \times \sum_{n = 0}^{I (i)} \frac{H_{c} (n)}{N_{L}}, 0 \leq I (i) \leq B_{1} \\ (B_{1} + 1) + (B_{2} - B_{1} + 1) \sum_{n = B_{1} + 1}^{I (i)} \frac{H_{c} (n)}{N_{M}}, B_{1} + 1 \leq I (i) \leq B_{2} \\ (B_{2} + 1) + (L - B_{2} + 1) \sum_{n = B_{2} + 1}^{I (i)} \frac{H_{c} (n)}{N_{H}}, B_{2} + 1 \leq I (i) \end{matrix}

A_{1} = A_{o} \times n o r m a l i z e d (V_{e})

A_{r} = P \times N o r m a i l z e d (A_{1})

f S N R = \frac{M_{p a r a f o v e a} - M_{F A Z}}{σ_{F A Z}}

R A = \frac{M_{O u t e r} + 3 \times σ_{O u t e r}}{M_{I n n e r} + 3 \times σ_{I n n e r}}

		PR	rbPR	improvement
Superficial	VSA(mm²)	1.79 ± 0.21	2.30 ± 0.24	64.55%
	VC	0.96 ± 0.02	0.98 ± 0.01	2.08%
	fSNR	3.82 ± 0.91	5.85 ± 1.60	53.14%
Intermediate	VSA(mm²)	1.96 ± 0.24	2.54 ± 0.15	29.59%
	VC	0.93 ± 0.03	0.98 ± 0.01	5.37%
	fSNR	3.21 ± 0.92	5.82 ± 1.67	81.3%
Deep	VSA(mm²)	1.29 ± 0.34	1.93 ± 0.65	49.61%
	VC	0.80 ± 0.08	0.95 ± 0.05	18.75%
	fSNR	1.49 ± 0.80	4.6 ± 1.74	208.72%
Outer	RA	0.50 ± 0.09	0.37 ± 0.05	25.92%

Abstract

References

2016 (5)

2015 (7)

2014 (2)

2013 (1)

2012 (2)

1992 (1)

1990 (1)

Bailey, S. T.

Balaratnasingam, C.

Bhavsr, K.

Bhutto, I.

Campbell, J. P.

Chan, G.

Cringle, S. J.

Dongye, C.

Flaxel, C. J.

Fujimoto, J. G.

Gao, S. S.

Hornegger, J.

Huang, D.

Hwang, T. S.

Jia, Y.

Kapoor, R.

Klein, M. L.

Kraus, M. F.

Lam, L.

Lauer, A.

Lauer, A. K.

Lee, S.-W.

Li, D.

Lin, P.

Liu, G.

Liu, J. J.

Liu, L.

Lu, C. D.

Lumbroso, B.

Lutty, G.

Lutty, G. A.

McAllister, I. L.

McClintic, S. M.

Morgan, W. H.

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Pechauer, A. D.

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Yu, D.-Y.

Yu, P. K.

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