Abstract

We present a method of OCT angiography (OCTA) data filtering for noise suppression and improved visualization of the retinal vascular networks in en face projection images. In our approach, we use a set of filters applied in three orthogonal axes in the three-dimensional (3-D) data sets. Minimization of artifacts generated in B-scan–wise data processing is accomplished by filtering the cross-sections along the slow scanning axis. A-scans are de-noised by axial filtering. The core of the method is the application of directional filtering to the C-scans, i.e. one-pixel thick sections of the 3-D data set, perpendicular to the direction of the scanning OCT beam. The method uses a concept of structuring, directional kernels of shapes matching the geometry of the image features. We use rotating ellipses to find the most likely local orientation of the vessels and use the best matching ellipses for median filtering of the C-scans. We demonstrate our approach in the imaging of a normal human eye with laboratory-grade spectral-domain OCT setup. The “field performance” is demonstrated in imaging of diabetic retinopathy cases with a commercial OCT device. The absolute complex differences method is used for the generation of OCTA images from the data collected in the most noise-wise unfavorable OCTA scanning regime–two frame scanning.

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

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References

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2018 (1)

R. F. Spaide, J. G. Fujimoto, N. K. Waheed, S. R. Sadda, and G. Staurenghi, “Optical coherence tomography angiography,” Prog. Retin. Eye Res. 64, 1–55 (2018).
[Crossref] [PubMed]

2017 (4)

2016 (8)

Z. Chu, J. Lin, C. Gao, C. Xin, Q. Zhang, C.-L. Chen, L. Roisman, G. Gregori, P. J. Rosenfeld, and R. K. Wang, “Quantitative assessment of the retinal microvasculature using optical coherence tomography angiography,” J. Biomed. Opt. 21(6), 66008 (2016).
[Crossref] [PubMed]

I. Gorczynska, J. V. Migacz, R. J. Zawadzki, A. G. Capps, and J. S. Werner, “Comparison of amplitude-decorrelation, speckle-variance and phase-variance OCT angiography methods for imaging the human retina and choroid,” Biomed. Opt. Express 7(3), 911–942 (2016).
[Crossref] [PubMed]

P. Zang, G. Liu, M. Zhang, C. Dongye, J. Wang, A. D. Pechauer, T. S. Hwang, D. J. Wilson, D. Huang, D. Li, and Y. Jia, “Automated motion correction using parallel-strip registration for wide-field en face OCT angiogram,” Biomed. Opt. Express 7(7), 2823–2836 (2016).
[Crossref] [PubMed]

P. Li, Y. Cheng, P. Li, L. Zhou, Z. Ding, Y. Ni, and C. Pan, “Hybrid averaging offers high-flow contrast by cost apportionment among imaging time, axial, and lateral resolution in optical coherence tomography angiography,” Opt. Lett. 41(17), 3944–3947 (2016).
[Crossref] [PubMed]

P. Li, Y. Cheng, L. Zhou, C. Pan, Z. Ding, and P. Li, “Single-shot angular compounded optical coherence tomography angiography by splitting full-space B-scan modulation spectrum for flow contrast enhancement,” Opt. Lett. 41(5), 1058–1061 (2016).
[Crossref] [PubMed]

S. Makita, K. Kurokawa, Y.-J. Hong, M. Miura, and Y. Yasuno, “Noise-immune complex correlation for optical coherence angiography based on standard and Jones matrix optical coherence tomography,” Biomed. Opt. Express 7(4), 1525–1548 (2016).
[Crossref] [PubMed]

S. B. Ploner, E. M. Moult, W. Choi, N. K. Waheed, B. Lee, E. A. Novais, E. D. Cole, B. Potsaid, L. Husvogt, J. Schottenhamml, A. Maier, P. J. Rosenfeld, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “Toward quantitative OCT angiography: visualizing blood flow speeds in ocular pathology using variable interscan time analysis (VISTA),” Retina 36(Suppl 1), S118–S126 (2016).
[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 (2016).
[Crossref] [PubMed]

2015 (3)

2014 (4)

D. M. Schwartz, J. Fingler, D. Y. Kim, R. J. Zawadzki, L. S. Morse, S. S. Park, S. E. Fraser, and J. S. Werner, “Phase-variance optical coherence tomography: a technique for noninvasive angiography,” Ophthalmology 121(1), 180–187 (2014).
[Crossref] [PubMed]

N. Uribe-Patarroyo, M. Villiger, and B. E. Bouma, “Quantitative technique for robust and noise-tolerant speed measurements based on speckle decorrelation in optical coherence tomography,” Opt. Express 22(20), 24411–24429 (2014).
[Crossref] [PubMed]

J. Xu, K. Wong, Y. Jian, and M. V. Sarunic, “Real-time acquisition and display of flow contrast using speckle variance optical coherence tomography in a graphics processing unit,” J. Biomed. Opt. 19(2), 026001 (2014).
[Crossref] [PubMed]

M. F. Kraus, J. J. Liu, J. Schottenhamml, C.-L. Chen, A. Budai, L. Branchini, T. Ko, H. Ishikawa, G. Wollstein, J. Schuman, J. S. Duker, J. G. Fujimoto, and J. Hornegger, “Quantitative 3D-OCT motion correction with tilt and illumination correction, robust similarity measure and regularization,” Biomed. Opt. Express 5(8), 2591–2613 (2014).
[Crossref] [PubMed]

2013 (1)

2012 (5)

2011 (1)

E. Jonathan, J. Enfield, and M. J. Leahy, “Correlation mapping method for generating microcirculation morphology from optical coherence tomography (OCT) intensity images,” J. Biophotonics 4(9), 583–587 (2011).
[PubMed]

2010 (2)

2009 (2)

2008 (2)

2007 (3)

2006 (2)

2000 (1)

C. Garnica, F. Boochs, and M. Twardochlib, “A new approach to edge-preserving smoothing for edge extraction and image segmentation,” International Archives of Photogrammetry and Remote Sensing 33(B3/1; PART 3), 320–325 (2000).

1998 (1)

Y. Sato, S. Nakajima, N. Shiraga, H. Atsumi, S. Yoshida, T. Koller, G. Gerig, and R. Kikinis, “Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images,” Med. Image Anal. 2(2), 143–168 (1998).
[Crossref] [PubMed]

1997 (1)

M. M. Orkisz, C. Bresson, I. E. Magnin, O. Champin, and P. C. Douek, “Improved vessel visualization in MR angiography by nonlinear anisotropic filtering,” Magn. Reson. Med. 37(6), 914–919 (1997).
[Crossref] [PubMed]

1995 (1)

Y. P. Du, D. L. Parker, and W. L. Davis, “Vessel enhancement filtering in three-dimensional MR angiography,” J. Magn. Reson. Imaging 5(3), 353–359 (1995).
[Crossref] [PubMed]

Agrawal, A.

An, L.

Andre, R.

C. Blatter, T. Klein, B. Grajciar, T. Schmoll, W. Wieser, R. Andre, R. Huber, and R. A. Leitgeb, “Ultrahigh-speed non-invasive widefield angiography,” J. Biomed. Opt. 17(7), 0705051 (2012).
[Crossref] [PubMed]

Atsumi, H.

Y. Sato, S. Nakajima, N. Shiraga, H. Atsumi, S. Yoshida, T. Koller, G. Gerig, and R. Kikinis, “Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images,” Med. Image Anal. 2(2), 143–168 (1998).
[Crossref] [PubMed]

Bachmann, A. H.

Bailey, S. T.

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 (2016).
[Crossref] [PubMed]

Balaratnasingam, C.

M. Heisler, S. Lee, Z. Mammo, Y. Jian, M. Ju, A. Merkur, E. Navajas, C. Balaratnasingam, M. F. Beg, and M. V. Sarunic, “Strip-based registration of serially acquired optical coherence tomography angiography,” J. Biomed. Opt. 22(3), 036007 (2017).
[Crossref] [PubMed]

Barry, S.

Beg, M. F.

M. Heisler, S. Lee, Z. Mammo, Y. Jian, M. Ju, A. Merkur, E. Navajas, C. Balaratnasingam, M. F. Beg, and M. V. Sarunic, “Strip-based registration of serially acquired optical coherence tomography angiography,” J. Biomed. Opt. 22(3), 036007 (2017).
[Crossref] [PubMed]

Bieganowski, L.

Blatter, C.

C. Blatter, T. Klein, B. Grajciar, T. Schmoll, W. Wieser, R. Andre, R. Huber, and R. A. Leitgeb, “Ultrahigh-speed non-invasive widefield angiography,” J. Biomed. Opt. 17(7), 0705051 (2012).
[Crossref] [PubMed]

A. H. Bachmann, M. L. Villiger, C. Blatter, T. Lasser, and R. A. Leitgeb, “Resonant Doppler flow imaging and optical vivisection of retinal blood vessels,” Opt. Express 15(2), 408–422 (2007).
[Crossref] [PubMed]

Boas, D. A.

Boochs, F.

C. Garnica, F. Boochs, and M. Twardochlib, “A new approach to edge-preserving smoothing for edge extraction and image segmentation,” International Archives of Photogrammetry and Remote Sensing 33(B3/1; PART 3), 320–325 (2000).

Boretsky, A.

Bouma, B. E.

Braaf, B.

Branchini, L.

Bresson, C.

M. M. Orkisz, C. Bresson, I. E. Magnin, O. Champin, and P. C. Douek, “Improved vessel visualization in MR angiography by nonlinear anisotropic filtering,” Magn. Reson. Med. 37(6), 914–919 (1997).
[Crossref] [PubMed]

Budai, A.

Bukowska, D.

Cable, A.

Cable, A. E.

Capps, A. G.

Champin, O.

M. M. Orkisz, C. Bresson, I. E. Magnin, O. Champin, and P. C. Douek, “Improved vessel visualization in MR angiography by nonlinear anisotropic filtering,” Magn. Reson. Med. 37(6), 914–919 (1997).
[Crossref] [PubMed]

Chen, C.-L.

C.-L. Chen and R. K. Wang, “Optical coherence tomography based angiography [Invited],” Biomed. Opt. Express 8(2), 1056–1082 (2017).
[Crossref] [PubMed]

Z. Chu, J. Lin, C. Gao, C. Xin, Q. Zhang, C.-L. Chen, L. Roisman, G. Gregori, P. J. Rosenfeld, and R. K. Wang, “Quantitative assessment of the retinal microvasculature using optical coherence tomography angiography,” J. Biomed. Opt. 21(6), 66008 (2016).
[Crossref] [PubMed]

A. Zhang, Q. Zhang, C.-L. Chen, and R. K. Wang, “Methods and algorithms for optical coherence tomography-based angiography: a review and comparison,” J. Biomed. Opt. 20(10), 100901 (2015).
[Crossref] [PubMed]

M. F. Kraus, J. J. Liu, J. Schottenhamml, C.-L. Chen, A. Budai, L. Branchini, T. Ko, H. Ishikawa, G. Wollstein, J. Schuman, J. S. Duker, J. G. Fujimoto, and J. Hornegger, “Quantitative 3D-OCT motion correction with tilt and illumination correction, robust similarity measure and regularization,” Biomed. Opt. Express 5(8), 2591–2613 (2014).
[Crossref] [PubMed]

Cheng, Y.

Chiu, S. J.

Choi, W.

S. B. Ploner, E. M. Moult, W. Choi, N. K. Waheed, B. Lee, E. A. Novais, E. D. Cole, B. Potsaid, L. Husvogt, J. Schottenhamml, A. Maier, P. J. Rosenfeld, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “Toward quantitative OCT angiography: visualizing blood flow speeds in ocular pathology using variable interscan time analysis (VISTA),” Retina 36(Suppl 1), S118–S126 (2016).
[Crossref] [PubMed]

Chu, Z.

Z. Chu, J. Lin, C. Gao, C. Xin, Q. Zhang, C.-L. Chen, L. Roisman, G. Gregori, P. J. Rosenfeld, and R. K. Wang, “Quantitative assessment of the retinal microvasculature using optical coherence tomography angiography,” J. Biomed. Opt. 21(6), 66008 (2016).
[Crossref] [PubMed]

Cole, E. D.

S. B. Ploner, E. M. Moult, W. Choi, N. K. Waheed, B. Lee, E. A. Novais, E. D. Cole, B. Potsaid, L. Husvogt, J. Schottenhamml, A. Maier, P. J. Rosenfeld, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “Toward quantitative OCT angiography: visualizing blood flow speeds in ocular pathology using variable interscan time analysis (VISTA),” Retina 36(Suppl 1), S118–S126 (2016).
[Crossref] [PubMed]

Davis, W. L.

Y. P. Du, D. L. Parker, and W. L. Davis, “Vessel enhancement filtering in three-dimensional MR angiography,” J. Magn. Reson. Imaging 5(3), 353–359 (1995).
[Crossref] [PubMed]

de Boer, J. F.

Ding, Z.

Dongye, C.

Douek, P. C.

M. M. Orkisz, C. Bresson, I. E. Magnin, O. Champin, and P. C. Douek, “Improved vessel visualization in MR angiography by nonlinear anisotropic filtering,” Magn. Reson. Med. 37(6), 914–919 (1997).
[Crossref] [PubMed]

Du, Y. P.

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S. B. Ploner, E. M. Moult, W. Choi, N. K. Waheed, B. Lee, E. A. Novais, E. D. Cole, B. Potsaid, L. Husvogt, J. Schottenhamml, A. Maier, P. J. Rosenfeld, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “Toward quantitative OCT angiography: visualizing blood flow speeds in ocular pathology using variable interscan time analysis (VISTA),” Retina 36(Suppl 1), S118–S126 (2016).
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Fraser, S. E.

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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 (2016).
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C. Garnica, F. Boochs, and M. Twardochlib, “A new approach to edge-preserving smoothing for edge extraction and image segmentation,” International Archives of Photogrammetry and Remote Sensing 33(B3/1; PART 3), 320–325 (2000).

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Y. Sato, S. Nakajima, N. Shiraga, H. Atsumi, S. Yoshida, T. Koller, G. Gerig, and R. Kikinis, “Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images,” Med. Image Anal. 2(2), 143–168 (1998).
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Z. Chu, J. Lin, C. Gao, C. Xin, Q. Zhang, C.-L. Chen, L. Roisman, G. Gregori, P. J. Rosenfeld, and R. K. Wang, “Quantitative assessment of the retinal microvasculature using optical coherence tomography angiography,” J. Biomed. Opt. 21(6), 66008 (2016).
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S. B. Ploner, E. M. Moult, W. Choi, N. K. Waheed, B. Lee, E. A. Novais, E. D. Cole, B. Potsaid, L. Husvogt, J. Schottenhamml, A. Maier, P. J. Rosenfeld, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “Toward quantitative OCT angiography: visualizing blood flow speeds in ocular pathology using variable interscan time analysis (VISTA),” Retina 36(Suppl 1), S118–S126 (2016).
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M. Heisler, S. Lee, Z. Mammo, Y. Jian, M. Ju, A. Merkur, E. Navajas, C. Balaratnasingam, M. F. Beg, and M. V. Sarunic, “Strip-based registration of serially acquired optical coherence tomography angiography,” J. Biomed. Opt. 22(3), 036007 (2017).
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Jiang, J. Y.

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E. Jonathan, J. Enfield, and M. J. Leahy, “Correlation mapping method for generating microcirculation morphology from optical coherence tomography (OCT) intensity images,” J. Biophotonics 4(9), 583–587 (2011).
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M. Heisler, S. Lee, Z. Mammo, Y. Jian, M. Ju, A. Merkur, E. Navajas, C. Balaratnasingam, M. F. Beg, and M. V. Sarunic, “Strip-based registration of serially acquired optical coherence tomography angiography,” J. Biomed. Opt. 22(3), 036007 (2017).
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Kikinis, R.

Y. Sato, S. Nakajima, N. Shiraga, H. Atsumi, S. Yoshida, T. Koller, G. Gerig, and R. Kikinis, “Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images,” Med. Image Anal. 2(2), 143–168 (1998).
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D. M. Schwartz, J. Fingler, D. Y. Kim, R. J. Zawadzki, L. S. Morse, S. S. Park, S. E. Fraser, and J. S. Werner, “Phase-variance optical coherence tomography: a technique for noninvasive angiography,” Ophthalmology 121(1), 180–187 (2014).
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Koller, T.

Y. Sato, S. Nakajima, N. Shiraga, H. Atsumi, S. Yoshida, T. Koller, G. Gerig, and R. Kikinis, “Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images,” Med. Image Anal. 2(2), 143–168 (1998).
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E. Jonathan, J. Enfield, and M. J. Leahy, “Correlation mapping method for generating microcirculation morphology from optical coherence tomography (OCT) intensity images,” J. Biophotonics 4(9), 583–587 (2011).
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S. B. Ploner, E. M. Moult, W. Choi, N. K. Waheed, B. Lee, E. A. Novais, E. D. Cole, B. Potsaid, L. Husvogt, J. Schottenhamml, A. Maier, P. J. Rosenfeld, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “Toward quantitative OCT angiography: visualizing blood flow speeds in ocular pathology using variable interscan time analysis (VISTA),” Retina 36(Suppl 1), S118–S126 (2016).
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Lee, K.

Lee, S.

M. Heisler, S. Lee, Z. Mammo, Y. Jian, M. Ju, A. Merkur, E. Navajas, C. Balaratnasingam, M. F. Beg, and M. V. Sarunic, “Strip-based registration of serially acquired optical coherence tomography angiography,” J. Biomed. Opt. 22(3), 036007 (2017).
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Leung, M. K. K.

Li, D.

Li, P.

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S. B. Ploner, E. M. Moult, W. Choi, N. K. Waheed, B. Lee, E. A. Novais, E. D. Cole, B. Potsaid, L. Husvogt, J. Schottenhamml, A. Maier, P. J. Rosenfeld, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “Toward quantitative OCT angiography: visualizing blood flow speeds in ocular pathology using variable interscan time analysis (VISTA),” Retina 36(Suppl 1), S118–S126 (2016).
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Malukiewicz, G.

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M. Heisler, S. Lee, Z. Mammo, Y. Jian, M. Ju, A. Merkur, E. Navajas, C. Balaratnasingam, M. F. Beg, and M. V. Sarunic, “Strip-based registration of serially acquired optical coherence tomography angiography,” J. Biomed. Opt. 22(3), 036007 (2017).
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Merkur, A.

M. Heisler, S. Lee, Z. Mammo, Y. Jian, M. Ju, A. Merkur, E. Navajas, C. Balaratnasingam, M. F. Beg, and M. V. Sarunic, “Strip-based registration of serially acquired optical coherence tomography angiography,” J. Biomed. Opt. 22(3), 036007 (2017).
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D. M. Schwartz, J. Fingler, D. Y. Kim, R. J. Zawadzki, L. S. Morse, S. S. Park, S. E. Fraser, and J. S. Werner, “Phase-variance optical coherence tomography: a technique for noninvasive angiography,” Ophthalmology 121(1), 180–187 (2014).
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S. B. Ploner, E. M. Moult, W. Choi, N. K. Waheed, B. Lee, E. A. Novais, E. D. Cole, B. Potsaid, L. Husvogt, J. Schottenhamml, A. Maier, P. J. Rosenfeld, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “Toward quantitative OCT angiography: visualizing blood flow speeds in ocular pathology using variable interscan time analysis (VISTA),” Retina 36(Suppl 1), S118–S126 (2016).
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Y. Sato, S. Nakajima, N. Shiraga, H. Atsumi, S. Yoshida, T. Koller, G. Gerig, and R. Kikinis, “Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images,” Med. Image Anal. 2(2), 143–168 (1998).
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M. Heisler, S. Lee, Z. Mammo, Y. Jian, M. Ju, A. Merkur, E. Navajas, C. Balaratnasingam, M. F. Beg, and M. V. Sarunic, “Strip-based registration of serially acquired optical coherence tomography angiography,” J. Biomed. Opt. 22(3), 036007 (2017).
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Novais, E. A.

S. B. Ploner, E. M. Moult, W. Choi, N. K. Waheed, B. Lee, E. A. Novais, E. D. Cole, B. Potsaid, L. Husvogt, J. Schottenhamml, A. Maier, P. J. Rosenfeld, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “Toward quantitative OCT angiography: visualizing blood flow speeds in ocular pathology using variable interscan time analysis (VISTA),” Retina 36(Suppl 1), S118–S126 (2016).
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M. M. Orkisz, C. Bresson, I. E. Magnin, O. Champin, and P. C. Douek, “Improved vessel visualization in MR angiography by nonlinear anisotropic filtering,” Magn. Reson. Med. 37(6), 914–919 (1997).
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Pan, C.

Park, S. S.

D. M. Schwartz, J. Fingler, D. Y. Kim, R. J. Zawadzki, L. S. Morse, S. S. Park, S. E. Fraser, and J. S. Werner, “Phase-variance optical coherence tomography: a technique for noninvasive angiography,” Ophthalmology 121(1), 180–187 (2014).
[Crossref] [PubMed]

Parker, D. L.

Y. P. Du, D. L. Parker, and W. L. Davis, “Vessel enhancement filtering in three-dimensional MR angiography,” J. Magn. Reson. Imaging 5(3), 353–359 (1995).
[Crossref] [PubMed]

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Ploner, S. B.

S. B. Ploner, E. M. Moult, W. Choi, N. K. Waheed, B. Lee, E. A. Novais, E. D. Cole, B. Potsaid, L. Husvogt, J. Schottenhamml, A. Maier, P. J. Rosenfeld, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “Toward quantitative OCT angiography: visualizing blood flow speeds in ocular pathology using variable interscan time analysis (VISTA),” Retina 36(Suppl 1), S118–S126 (2016).
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S. B. Ploner, E. M. Moult, W. Choi, N. K. Waheed, B. Lee, E. A. Novais, E. D. Cole, B. Potsaid, L. Husvogt, J. Schottenhamml, A. Maier, P. J. Rosenfeld, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “Toward quantitative OCT angiography: visualizing blood flow speeds in ocular pathology using variable interscan time analysis (VISTA),” Retina 36(Suppl 1), S118–S126 (2016).
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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).
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Radhakrishnan, H.

Ren, Q.

Roisman, L.

Z. Chu, J. Lin, C. Gao, C. Xin, Q. Zhang, C.-L. Chen, L. Roisman, G. Gregori, P. J. Rosenfeld, and R. K. Wang, “Quantitative assessment of the retinal microvasculature using optical coherence tomography angiography,” J. Biomed. Opt. 21(6), 66008 (2016).
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S. B. Ploner, E. M. Moult, W. Choi, N. K. Waheed, B. Lee, E. A. Novais, E. D. Cole, B. Potsaid, L. Husvogt, J. Schottenhamml, A. Maier, P. J. Rosenfeld, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “Toward quantitative OCT angiography: visualizing blood flow speeds in ocular pathology using variable interscan time analysis (VISTA),” Retina 36(Suppl 1), S118–S126 (2016).
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Sadda, S. R.

R. F. Spaide, J. G. Fujimoto, N. K. Waheed, S. R. Sadda, and G. Staurenghi, “Optical coherence tomography angiography,” Prog. Retin. Eye Res. 64, 1–55 (2018).
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M. Heisler, S. Lee, Z. Mammo, Y. Jian, M. Ju, A. Merkur, E. Navajas, C. Balaratnasingam, M. F. Beg, and M. V. Sarunic, “Strip-based registration of serially acquired optical coherence tomography angiography,” J. Biomed. Opt. 22(3), 036007 (2017).
[Crossref] [PubMed]

J. Xu, K. Wong, Y. Jian, and M. V. Sarunic, “Real-time acquisition and display of flow contrast using speckle variance optical coherence tomography in a graphics processing unit,” J. Biomed. Opt. 19(2), 026001 (2014).
[Crossref] [PubMed]

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Sato, Y.

Y. Sato, S. Nakajima, N. Shiraga, H. Atsumi, S. Yoshida, T. Koller, G. Gerig, and R. Kikinis, “Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images,” Med. Image Anal. 2(2), 143–168 (1998).
[Crossref] [PubMed]

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C. Blatter, T. Klein, B. Grajciar, T. Schmoll, W. Wieser, R. Andre, R. Huber, and R. A. Leitgeb, “Ultrahigh-speed non-invasive widefield angiography,” J. Biomed. Opt. 17(7), 0705051 (2012).
[Crossref] [PubMed]

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S. B. Ploner, E. M. Moult, W. Choi, N. K. Waheed, B. Lee, E. A. Novais, E. D. Cole, B. Potsaid, L. Husvogt, J. Schottenhamml, A. Maier, P. J. Rosenfeld, J. S. Duker, J. Hornegger, and J. G. Fujimoto, “Toward quantitative OCT angiography: visualizing blood flow speeds in ocular pathology using variable interscan time analysis (VISTA),” Retina 36(Suppl 1), S118–S126 (2016).
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M. F. Kraus, J. J. Liu, J. Schottenhamml, C.-L. Chen, A. Budai, L. Branchini, T. Ko, H. Ishikawa, G. Wollstein, J. Schuman, J. S. Duker, J. G. Fujimoto, and J. Hornegger, “Quantitative 3D-OCT motion correction with tilt and illumination correction, robust similarity measure and regularization,” Biomed. Opt. Express 5(8), 2591–2613 (2014).
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Schuman, J.

Schwartz, D.

Schwartz, D. M.

D. M. Schwartz, J. Fingler, D. Y. Kim, R. J. Zawadzki, L. S. Morse, S. S. Park, S. E. Fraser, and J. S. Werner, “Phase-variance optical coherence tomography: a technique for noninvasive angiography,” Ophthalmology 121(1), 180–187 (2014).
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Y. Sato, S. Nakajima, N. Shiraga, H. Atsumi, S. Yoshida, T. Koller, G. Gerig, and R. Kikinis, “Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images,” Med. Image Anal. 2(2), 143–168 (1998).
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Spaide, R. F.

R. F. Spaide, J. G. Fujimoto, N. K. Waheed, S. R. Sadda, and G. Staurenghi, “Optical coherence tomography angiography,” Prog. Retin. Eye Res. 64, 1–55 (2018).
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Standish, B. A.

Staurenghi, G.

R. F. Spaide, J. G. Fujimoto, N. K. Waheed, S. R. Sadda, and G. Staurenghi, “Optical coherence tomography angiography,” Prog. Retin. Eye Res. 64, 1–55 (2018).
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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 (2016).
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C. Garnica, F. Boochs, and M. Twardochlib, “A new approach to edge-preserving smoothing for edge extraction and image segmentation,” International Archives of Photogrammetry and Remote Sensing 33(B3/1; PART 3), 320–325 (2000).

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Vitkin, I. A.

Waheed, N. K.

R. F. Spaide, J. G. Fujimoto, N. K. Waheed, S. R. Sadda, and G. Staurenghi, “Optical coherence tomography angiography,” Prog. Retin. Eye Res. 64, 1–55 (2018).
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Optopol. Technology, “Revo NX,” http://optopol.com/products/revo-nx .

Supplementary Material (1)

NameDescription
» Visualization 1       Illustration of the best-ellipse search procedure in an example C-scan. The lengths of the green lines are proportional to the error function values. The lower the value of the metric, the shorter the green line and the more likely the orientation of

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Figures (6)

Fig. 1
Fig. 1 Three-dimensional data sets. a. Structural data set used for segmentation of the outer plexiform layer. The fitted surface was used for selection of depth positions of en face projections as indicated by the yellow and blue lines. b. OCTA data set indicating the orientation of three planes of interest used in our data processing. Green outlines – B-scans, XZ planes parallel to the fast scanning axis; blue – YZ planes, parallel to the slow scan axis; pink – C-scans, XY planes, perpendicular to the scanning beam. c. OCTA en face projections of the retinal vessels and the inner capillary plexus were generated as maximum intensity projection between the yellow lines. An example angiogram is schematically shown with yellow outline. The angiogram of the outer capillary plexus was generated between the blue lines.
Fig. 2
Fig. 2 Data filtering pipeline.
Fig. 3
Fig. 3 Demonstration of the best-ellipse search procedure in selected locations of an example C-scan (XY slice through the 3-D data set with the thickness of 1 pixel). The inset illustrates the discretization of the ellipses used as the filter kernels. Error functions (Err) are used as a metric to find the most likely match from the collection of ellipses oriented along the directions of the green lines. The lengths of the green lines are proportional to the error function values. The lower the value of the metric, the shorter the green line and the more likely the orientation of the ellipse follows the local orientation of vessels. The pink ellipses are the best choices according to our procedure. They are shown together with pink lines indicating their error functions. The best-ellipse search is performed automatically at each pixel of each C-scan prior to generation of en face projections. The scale bar indicates OCTA signal intensity in the floating point, 32-bit data representation. The image size is 2 x 2 mm. The associated media file (Visualization 1) demonstrated the best-ellipse search procedure concept in subsequent C-scans.
Fig. 4
Fig. 4 OCT angiograms of a normal eye obtained with Revo NX, scan protocol 1. Top row - the superficial vascular plexus. Bottom row – deep capillary plexus. Left – unfiltered data. Right – after application of the elliptical directional filtering processing pipeline. Insets in the middle – enlarged regions of interest comparing the effects of the filtering procedure. Image size: 3 x 3 mm, insets size: 0.32 x 0.32 mm.
Fig. 5
Fig. 5 OCT angiograms of a normal eye obtained with a research-grade OCT system. Top row - the superficial vascular plexus. Bottom row – deep capillary plexus. Left – unfiltered data. Right – after application of the elliptical directional filtering processing pipeline. The bright spot in the center is a central foveal reflection. Insets in the middle – enlarged regions of interest comparing the effects of the filtering procedure. Image size: 2 x 2 mm, insets size: 0.32 x 0.32 mm.
Fig. 6
Fig. 6 OCT angiograms of diabetic retinopathy cases obtained with Revo NX. Left row – not filtered images. Right row – angiograms after application of the elliptical directional median filtering. Case 1: non-proliferative, early stage; scan protocol 1. Case 2: non-proliferative, enlarged foveal avascular zone, decreased vascular density visible. Case 3: proliferative, after panretinal laser photocoagulation, nonperfusion areas and tortuous vessels present. Pink circle and arrows – foveal avascular zone. Green arrows – non-perfusion areas. Blue arrows – microaneurysms. Case 1 and 2 – image size 3 x 3 mm (scan protocol 1 in Table 2). Case 3 – image size 5 x5 mm (scan protocol 2 in Table 2).

Tables (5)

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Table 1 OCT angiography scan protocol – Revo NX

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Table 2 OCT angiography scan protocol – research grade OCT system

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Table 3 Values of the filtering parameters

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Table 4 Demonstration of the image filtering steps in the angiograms of the superficial retinal vascular plexus of a normal eye. Images obtained with the research grade OCT setup.

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Table 5 Influence of the elliptical kernel parameter values on the OCTA en face projections. Parameters and evaluation-metrics values are given below the images. Images obtained with the research grade OCT setup.

Equations (6)

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I OCTA ( x,z )= ( 1 M1 n=0 M2 | A( x,z, t m+1 )A( x,z, t m ) | ) 2 ,
E n =Ellipse( a,c, β n ), β n = nπ N +α, where:
Er r n,z ( x,y )= σ n 2 ( x,y ) μ n 2 ( x,y ) σ z + σ n 2 ( x,y ) , where:
n z BEST ( x,y )= argmin n 0,N1 Er r n,z ( x,y ) E z BEST ( x,y )= E n z BEST ( x,y ) ,
v FILTERED ( x,y,z )=median( { v( x ˜ , y ˜ ,z ), ( x ˜ , y ˜ ) E z BEST ( x,y ) } ),
VCont( A,B )= Number of vascular fragments in A Number of vascular fragments in B = N( A ) N( B )