Abstract

We present a novel fully automated algorithm for the detection of retinal diseases via optical coherence tomography (OCT) imaging. Our algorithm utilizes multiscale histograms of oriented gradient descriptors as feature vectors of a support vector machine based classifier. The spectral domain OCT data sets used for cross-validation consisted of volumetric scans acquired from 45 subjects: 15 normal subjects, 15 patients with dry age-related macular degeneration (AMD), and 15 patients with diabetic macular edema (DME). Our classifier correctly identified 100% of cases with AMD, 100% cases with DME, and 86.67% cases of normal subjects. This algorithm is a potentially impactful tool for the remote diagnosis of ophthalmic diseases.

© 2014 Optical Society of America

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References

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    [Crossref] [PubMed]
  3. M. R. Hee, J. A. Izatt, E. A. Swanson, D. Huang, J. S. Schuman, C. P. Lin, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography of the human retina,” Arch. Ophthalmol. 113(3), 325–332 (1995).
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  23. D. C. Fernández, “Delineating Fluid-Filled Region Boundaries in Optical Coherence Tomography Images of the Retina,” IEEE Trans. Med. Imaging 24(8), 929–945 (2005).
    [Crossref] [PubMed]
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    [Crossref] [PubMed]
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    [Crossref] [PubMed]
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    [Crossref]
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    [Crossref] [PubMed]
  36. M. A. Mayer, A. Borsdorf, M. Wagner, J. Hornegger, C. Y. Mardin, and R. P. Tornow, “Wavelet denoising of multiframe optical coherence tomography data,” Biomed. Opt. Express 3(3), 572–589 (2012).
    [Crossref] [PubMed]
  37. K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering,” IEEE Trans. Image Process. 16(8), 2080–2095 (2007).
    [Crossref] [PubMed]
  38. A. N. Kuo, R. P. McNabb, S. J. Chiu, M. A. El-Dairi, S. Farsiu, C. A. Toth, and J. A. Izatt, “Correction of Ocular Shape in Retinal Optical Coherence Tomography and Effect on Current Clinical Measures,” Am. J. Ophthalmol. 156(2), 304–311 (2013).
    [Crossref] [PubMed]
  39. P. J. Burt and E. H. Adelson, “The Laplacian Pyramid as a Compact Image Code,” IEEE Trans. Commun. 31(4), 532–540 (1983).
    [Crossref]
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    [Crossref] [PubMed]

2014 (5)

A. Carass, A. Lang, M. Hauser, P. A. Calabresi, H. S. Ying, and J. L. Prince, “Multiple-object geometric deformable model for segmentation of macular OCT,” Biomed. Opt. Express 5(4), 1062–1074 (2014).
[Crossref] [PubMed]

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, and C. A. Toth, “Quantitative Classification of Eyes with and without Intermediate Age-related Macular Degeneration Using Optical Coherence Tomography,” Ophthalmology 121(1), 162–172 (2014).

G. M. Somfai, E. Tátrai, L. Laurik, B. Varga, V. Ölvedy, H. Jiang, J. Wang, W. E. Smiddy, A. Somogyi, and D. C. DeBuc, “Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes,” BMC Bioinformatics 15(1), 106 (2014).
[Crossref] [PubMed]

Y. Zhang, B. Zhang, F. Coenen, J. Xiao, and W. Lu, “One-class kernel subspace ensemble for medical image classification,” EURASIP J. Adv. Signal Process. 2014, 1–13 (2014).

P. P. Srinivasan, S. J. Heflin, J. A. Izatt, V. Y. Arshavsky, and S. Farsiu, “Automatic segmentation of up to ten layer boundaries in SD-OCT images of the mouse retina with and without missing layers due to pathology,” Biomed. Opt. Express 5(2), 348–365 (2014).
[Crossref] [PubMed]

2013 (6)

A. N. Kuo, R. P. McNabb, S. J. Chiu, M. A. El-Dairi, S. Farsiu, C. A. Toth, and J. A. Izatt, “Correction of Ocular Shape in Retinal Optical Coherence Tomography and Effect on Current Clinical Measures,” Am. J. Ophthalmol. 156(2), 304–311 (2013).
[Crossref] [PubMed]

R. Koprowski, S. Teper, Z. Wróbel, and E. Wylegala, “Automatic analysis of selected choroidal diseases in OCT images of the eye fundus,” Biomed. Eng. Online 12(1), 117 (2013).
[Crossref] [PubMed]

A. Lang, A. Carass, M. Hauser, E. S. Sotirchos, P. A. Calabresi, H. S. Ying, and J. L. Prince, “Retinal layer segmentation of macular OCT images using boundary classification,” Biomed. Opt. Express 4(7), 1133–1152 (2013).
[Crossref] [PubMed]

B. J. Antony, M. D. Abràmoff, M. M. Harper, W. Jeong, E. H. Sohn, Y. H. Kwon, R. Kardon, and M. K. Garvin, “A combined machine-learning and graph-based framework for the segmentation of retinal surfaces in SD-OCT volumes,” Biomed. Opt. Express 4(12), 2712–2728 (2013).
[Crossref] [PubMed]

C. Bowes Rickman, S. Farsiu, C. A. Toth, and M. Klingeborn, “Dry Age-Related Macular Degeneration: Mechanisms, Therapeutic Targets, and Imaging,” Invest. Ophthalmol. Vis. Sci. 54(14), ORSF68 (2013).
[Crossref] [PubMed]

J. Y. Lee, S. J. Chiu, P. Srinivasan, J. A. Izatt, C. A. Toth, S. Farsiu, and G. J. Jaffe, “Fully Automatic Software for Quantification of Retinal Thickness and Volume in Eyes with Diabetic Macular Edema from Images Acquired by Cirrus and Spectralis Spectral Domain Optical Coherence Tomography Machines,” Invest. Ophthalmol. Vis. Sci. 54, 7595–7602 (2013).
[Crossref] [PubMed]

2012 (5)

J. Yellowlees Douglas, A. D. Bhatwadekar, S. Li Calzi, L. C. Shaw, D. Carnegie, S. Caballero, Q. Li, A. W. Stitt, M. K. Raizada, and M. B. Grant, “Bone marrow-CNS connections: Implications in the pathogenesis of diabetic retinopathy,” Prog. Retin. Eye Res. 31(5), 481–494 (2012).
[Crossref] [PubMed]

S. J. Chiu, J. A. Izatt, R. V. O’Connell, K. P. Winter, C. A. Toth, and S. Farsiu, “Validated Automatic Segmentation of AMD Pathology Including Drusen and Geographic Atrophy in SD-OCT Images,” Invest. Ophthalmol. Vis. Sci. 53(1), 53–61 (2012).
[Crossref] [PubMed]

S. J. Chiu, C. A. Toth, C. Bowes Rickman, J. A. Izatt, and S. Farsiu, “Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming,” Biomed. Opt. Express 3(5), 1127–1140 (2012).
[Crossref] [PubMed]

L. Fang, S. Li, Q. Nie, J. A. Izatt, C. A. Toth, and S. Farsiu, “Sparsity based denoising of spectral domain optical coherence tomography images,” Biomed. Opt. Express 3(5), 927–942 (2012).
[Crossref] [PubMed]

M. A. Mayer, A. Borsdorf, M. Wagner, J. Hornegger, C. Y. Mardin, and R. P. Tornow, “Wavelet denoising of multiframe optical coherence tomography data,” Biomed. Opt. Express 3(3), 572–589 (2012).
[Crossref] [PubMed]

2011 (4)

Y.-Y. Liu, H. Ishikawa, M. Chen, G. Wollstein, J. S. Duker, J. G. Fujimoto, J. S. Schuman, and J. M. Rehg, “Computerized macular pathology diagnosis in spectral domain optical coherence tomography scans based on multiscale texture and shape features,” Invest. Ophthalmol. Vis. Sci. 52(11), 8316–8322 (2011).
[Crossref] [PubMed]

K. A. Vermeer, J. van der Schoot, H. G. Lemij, and J. F. de Boer, “Automated segmentation by pixel classification of retinal layers in ophthalmic OCT images,” Biomed. Opt. Express 2(6), 1743–1756 (2011).
[Crossref] [PubMed]

Q. Yang, C. A. Reisman, K. Chan, R. Ramachandran, A. Raza, and D. C. Hood, “Automated segmentation of outer retinal layers in macular OCT images of patients with retinitis pigmentosa,” Biomed. Opt. Express 2(9), 2493–2503 (2011).
[Crossref] [PubMed]

G. Gregori, F. Wang, P. J. Rosenfeld, Z. Yehoshua, N. Z. Gregori, B. J. Lujan, C. A. Puliafito, and W. J. Feuer, “Spectral domain optical coherence tomography imaging of drusen in nonexudative age-related macular degeneration,” Ophthalmology 118(7), 1373–1379 (2011).
[PubMed]

2010 (2)

2009 (2)

D. C. DeBuc, G. M. Somfai, S. Ranganathan, E. Tátrai, M. Ferencz, and C. A. Puliafito, “Reliability and reproducibility of macular segmentation using a custom-built optical coherence tomography retinal image analysis software,” J. Biomed. Opt. 14(6), 064023 (2009).
[Crossref] [PubMed]

A. Mishra, A. Wong, K. Bizheva, and D. A. Clausi, “Intra-retinal layer segmentation in optical coherence tomography images,” Opt. Express 17(26), 23719–23728 (2009).
[Crossref] [PubMed]

2008 (1)

O. Tan, G. Li, A. T.-H. Lu, R. Varma, and D. Huang, “Mapping of Macular Substructures with Optical Coherence Tomography for Glaucoma Diagnosis,” Ophthalmology 115(6), 949–956 (2008).

2007 (1)

K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering,” IEEE Trans. Image Process. 16(8), 2080–2095 (2007).
[Crossref] [PubMed]

2005 (6)

D. C. Fernández, “Delineating Fluid-Filled Region Boundaries in Optical Coherence Tomography Images of the Retina,” IEEE Trans. Med. Imaging 24(8), 929–945 (2005).
[Crossref] [PubMed]

M. Mujat, R. Chan, B. Cense, B. Park, C. Joo, T. Akkin, T. Chen, and J. de Boer, “Retinal nerve fiber layer thickness map determined from optical coherence tomography images,” Opt. Express 13(23), 9480–9491 (2005).
[Crossref] [PubMed]

D. Cabrera Fernández, H. M. Salinas, and C. A. Puliafito, “Automated detection of retinal layer structures on optical coherence tomography images,” Opt. Express 13(25), 10200–10216 (2005).
[Crossref] [PubMed]

F. A. Medeiros, L. M. Zangwill, C. Bowd, R. M. Vessani, R. Susanna, and R. N. Weinreb, “Evaluation of retinal nerve fiber layer, optic nerve head, and macular thickness measurements for glaucoma detection using optical coherence tomography,” Am. J. Ophthalmol. 139(1), 44–55 (2005).
[Crossref] [PubMed]

H. Ishikawa, D. M. Stein, G. Wollstein, S. Beaton, J. G. Fujimoto, and J. S. Schuman, “Macular Segmentation with Optical Coherence Tomography,” Invest. Ophthalmol. Vis. Sci. 46(6), 2012–2017 (2005).
[Crossref] [PubMed]

M. Shahidi, Z. Wang, and R. Zelkha, “Quantitative Thickness Measurement of Retinal Layers Imaged by Optical Coherence Tomography,” Am. J. Ophthalmol. 139(6), 1056–1061 (2005).
[Crossref] [PubMed]

2004 (1)

L. A. Paunescu, J. S. Schuman, L. L. Price, P. C. Stark, S. Beaton, H. Ishikawa, G. Wollstein, and J. G. Fujimoto, “Reproducibility of Nerve Fiber Thickness, Macular Thickness, and Optic Nerve Head Measurements Using StratusOCT,” Invest. Ophthalmol. Vis. Sci. 45(6), 1716–1724 (2004).
[Crossref] [PubMed]

2001 (1)

Age-Related Eye Disease Study Research Group, “A randomized, placebo-controlled, clinical trial of high-dose supplementation with vitamins C and E, beta carotene, and zinc for age-related macular degeneration and vision loss: AREDS report no. 8,” Arch. Ophthalmol. 119(10), 1417–1436 (2001).
[Crossref] [PubMed]

1995 (2)

M. R. Hee, J. A. Izatt, E. A. Swanson, D. Huang, J. S. Schuman, C. P. Lin, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography of the human retina,” Arch. Ophthalmol. 113(3), 325–332 (1995).
[Crossref] [PubMed]

C. Cortes and V. Vapnik, “Support-vector networks,” Mach. Learn. 20(3), 273–297 (1995).
[Crossref]

1983 (1)

P. J. Burt and E. H. Adelson, “The Laplacian Pyramid as a Compact Image Code,” IEEE Trans. Commun. 31(4), 532–540 (1983).
[Crossref]

Abràmoff, M. D.

Adelson, E. H.

P. J. Burt and E. H. Adelson, “The Laplacian Pyramid as a Compact Image Code,” IEEE Trans. Commun. 31(4), 532–540 (1983).
[Crossref]

Akkin, T.

Antony, B. J.

Arshavsky, V. Y.

Beaton, S.

H. Ishikawa, D. M. Stein, G. Wollstein, S. Beaton, J. G. Fujimoto, and J. S. Schuman, “Macular Segmentation with Optical Coherence Tomography,” Invest. Ophthalmol. Vis. Sci. 46(6), 2012–2017 (2005).
[Crossref] [PubMed]

L. A. Paunescu, J. S. Schuman, L. L. Price, P. C. Stark, S. Beaton, H. Ishikawa, G. Wollstein, and J. G. Fujimoto, “Reproducibility of Nerve Fiber Thickness, Macular Thickness, and Optic Nerve Head Measurements Using StratusOCT,” Invest. Ophthalmol. Vis. Sci. 45(6), 1716–1724 (2004).
[Crossref] [PubMed]

Bhatwadekar, A. D.

J. Yellowlees Douglas, A. D. Bhatwadekar, S. Li Calzi, L. C. Shaw, D. Carnegie, S. Caballero, Q. Li, A. W. Stitt, M. K. Raizada, and M. B. Grant, “Bone marrow-CNS connections: Implications in the pathogenesis of diabetic retinopathy,” Prog. Retin. Eye Res. 31(5), 481–494 (2012).
[Crossref] [PubMed]

Bizheva, K.

Borsdorf, A.

Bowd, C.

F. A. Medeiros, L. M. Zangwill, C. Bowd, R. M. Vessani, R. Susanna, and R. N. Weinreb, “Evaluation of retinal nerve fiber layer, optic nerve head, and macular thickness measurements for glaucoma detection using optical coherence tomography,” Am. J. Ophthalmol. 139(1), 44–55 (2005).
[Crossref] [PubMed]

Bowes Rickman, C.

C. Bowes Rickman, S. Farsiu, C. A. Toth, and M. Klingeborn, “Dry Age-Related Macular Degeneration: Mechanisms, Therapeutic Targets, and Imaging,” Invest. Ophthalmol. Vis. Sci. 54(14), ORSF68 (2013).
[Crossref] [PubMed]

S. J. Chiu, C. A. Toth, C. Bowes Rickman, J. A. Izatt, and S. Farsiu, “Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming,” Biomed. Opt. Express 3(5), 1127–1140 (2012).
[Crossref] [PubMed]

Burt, P. J.

P. J. Burt and E. H. Adelson, “The Laplacian Pyramid as a Compact Image Code,” IEEE Trans. Commun. 31(4), 532–540 (1983).
[Crossref]

Caballero, S.

J. Yellowlees Douglas, A. D. Bhatwadekar, S. Li Calzi, L. C. Shaw, D. Carnegie, S. Caballero, Q. Li, A. W. Stitt, M. K. Raizada, and M. B. Grant, “Bone marrow-CNS connections: Implications in the pathogenesis of diabetic retinopathy,” Prog. Retin. Eye Res. 31(5), 481–494 (2012).
[Crossref] [PubMed]

Cabrera Fernández, D.

Calabresi, P. A.

Carass, A.

Carnegie, D.

J. Yellowlees Douglas, A. D. Bhatwadekar, S. Li Calzi, L. C. Shaw, D. Carnegie, S. Caballero, Q. Li, A. W. Stitt, M. K. Raizada, and M. B. Grant, “Bone marrow-CNS connections: Implications in the pathogenesis of diabetic retinopathy,” Prog. Retin. Eye Res. 31(5), 481–494 (2012).
[Crossref] [PubMed]

Cense, B.

Chan, K.

Chan, R.

Chen, M.

Y.-Y. Liu, H. Ishikawa, M. Chen, G. Wollstein, J. S. Duker, J. G. Fujimoto, J. S. Schuman, and J. M. Rehg, “Computerized macular pathology diagnosis in spectral domain optical coherence tomography scans based on multiscale texture and shape features,” Invest. Ophthalmol. Vis. Sci. 52(11), 8316–8322 (2011).
[Crossref] [PubMed]

Chen, T.

Chiu, S. J.

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, and C. A. Toth, “Quantitative Classification of Eyes with and without Intermediate Age-related Macular Degeneration Using Optical Coherence Tomography,” Ophthalmology 121(1), 162–172 (2014).

A. N. Kuo, R. P. McNabb, S. J. Chiu, M. A. El-Dairi, S. Farsiu, C. A. Toth, and J. A. Izatt, “Correction of Ocular Shape in Retinal Optical Coherence Tomography and Effect on Current Clinical Measures,” Am. J. Ophthalmol. 156(2), 304–311 (2013).
[Crossref] [PubMed]

J. Y. Lee, S. J. Chiu, P. Srinivasan, J. A. Izatt, C. A. Toth, S. Farsiu, and G. J. Jaffe, “Fully Automatic Software for Quantification of Retinal Thickness and Volume in Eyes with Diabetic Macular Edema from Images Acquired by Cirrus and Spectralis Spectral Domain Optical Coherence Tomography Machines,” Invest. Ophthalmol. Vis. Sci. 54, 7595–7602 (2013).
[Crossref] [PubMed]

S. J. Chiu, J. A. Izatt, R. V. O’Connell, K. P. Winter, C. A. Toth, and S. Farsiu, “Validated Automatic Segmentation of AMD Pathology Including Drusen and Geographic Atrophy in SD-OCT Images,” Invest. Ophthalmol. Vis. Sci. 53(1), 53–61 (2012).
[Crossref] [PubMed]

S. J. Chiu, C. A. Toth, C. Bowes Rickman, J. A. Izatt, and S. Farsiu, “Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming,” Biomed. Opt. Express 3(5), 1127–1140 (2012).
[Crossref] [PubMed]

S. J. Chiu, X. T. Li, P. Nicholas, C. A. Toth, J. A. Izatt, and S. Farsiu, “Automatic segmentation of seven retinal layers in SDOCT images congruent with expert manual segmentation,” Opt. Express 18(18), 19413–19428 (2010).
[Crossref] [PubMed]

Clausi, D. A.

Coenen, F.

Y. Zhang, B. Zhang, F. Coenen, J. Xiao, and W. Lu, “One-class kernel subspace ensemble for medical image classification,” EURASIP J. Adv. Signal Process. 2014, 1–13 (2014).

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C. Cortes and V. Vapnik, “Support-vector networks,” Mach. Learn. 20(3), 273–297 (1995).
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K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering,” IEEE Trans. Image Process. 16(8), 2080–2095 (2007).
[Crossref] [PubMed]

de Boer, J.

de Boer, J. F.

DeBuc, D. C.

G. M. Somfai, E. Tátrai, L. Laurik, B. Varga, V. Ölvedy, H. Jiang, J. Wang, W. E. Smiddy, A. Somogyi, and D. C. DeBuc, “Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes,” BMC Bioinformatics 15(1), 106 (2014).
[Crossref] [PubMed]

D. C. DeBuc, G. M. Somfai, S. Ranganathan, E. Tátrai, M. Ferencz, and C. A. Puliafito, “Reliability and reproducibility of macular segmentation using a custom-built optical coherence tomography retinal image analysis software,” J. Biomed. Opt. 14(6), 064023 (2009).
[Crossref] [PubMed]

Duker, J. S.

Y.-Y. Liu, H. Ishikawa, M. Chen, G. Wollstein, J. S. Duker, J. G. Fujimoto, J. S. Schuman, and J. M. Rehg, “Computerized macular pathology diagnosis in spectral domain optical coherence tomography scans based on multiscale texture and shape features,” Invest. Ophthalmol. Vis. Sci. 52(11), 8316–8322 (2011).
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Egiazarian, K.

K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering,” IEEE Trans. Image Process. 16(8), 2080–2095 (2007).
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El-Dairi, M. A.

A. N. Kuo, R. P. McNabb, S. J. Chiu, M. A. El-Dairi, S. Farsiu, C. A. Toth, and J. A. Izatt, “Correction of Ocular Shape in Retinal Optical Coherence Tomography and Effect on Current Clinical Measures,” Am. J. Ophthalmol. 156(2), 304–311 (2013).
[Crossref] [PubMed]

Fang, L.

Farsiu, S.

P. P. Srinivasan, S. J. Heflin, J. A. Izatt, V. Y. Arshavsky, and S. Farsiu, “Automatic segmentation of up to ten layer boundaries in SD-OCT images of the mouse retina with and without missing layers due to pathology,” Biomed. Opt. Express 5(2), 348–365 (2014).
[Crossref] [PubMed]

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, and C. A. Toth, “Quantitative Classification of Eyes with and without Intermediate Age-related Macular Degeneration Using Optical Coherence Tomography,” Ophthalmology 121(1), 162–172 (2014).

C. Bowes Rickman, S. Farsiu, C. A. Toth, and M. Klingeborn, “Dry Age-Related Macular Degeneration: Mechanisms, Therapeutic Targets, and Imaging,” Invest. Ophthalmol. Vis. Sci. 54(14), ORSF68 (2013).
[Crossref] [PubMed]

A. N. Kuo, R. P. McNabb, S. J. Chiu, M. A. El-Dairi, S. Farsiu, C. A. Toth, and J. A. Izatt, “Correction of Ocular Shape in Retinal Optical Coherence Tomography and Effect on Current Clinical Measures,” Am. J. Ophthalmol. 156(2), 304–311 (2013).
[Crossref] [PubMed]

J. Y. Lee, S. J. Chiu, P. Srinivasan, J. A. Izatt, C. A. Toth, S. Farsiu, and G. J. Jaffe, “Fully Automatic Software for Quantification of Retinal Thickness and Volume in Eyes with Diabetic Macular Edema from Images Acquired by Cirrus and Spectralis Spectral Domain Optical Coherence Tomography Machines,” Invest. Ophthalmol. Vis. Sci. 54, 7595–7602 (2013).
[Crossref] [PubMed]

S. J. Chiu, J. A. Izatt, R. V. O’Connell, K. P. Winter, C. A. Toth, and S. Farsiu, “Validated Automatic Segmentation of AMD Pathology Including Drusen and Geographic Atrophy in SD-OCT Images,” Invest. Ophthalmol. Vis. Sci. 53(1), 53–61 (2012).
[Crossref] [PubMed]

L. Fang, S. Li, Q. Nie, J. A. Izatt, C. A. Toth, and S. Farsiu, “Sparsity based denoising of spectral domain optical coherence tomography images,” Biomed. Opt. Express 3(5), 927–942 (2012).
[Crossref] [PubMed]

S. J. Chiu, C. A. Toth, C. Bowes Rickman, J. A. Izatt, and S. Farsiu, “Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming,” Biomed. Opt. Express 3(5), 1127–1140 (2012).
[Crossref] [PubMed]

S. J. Chiu, X. T. Li, P. Nicholas, C. A. Toth, J. A. Izatt, and S. Farsiu, “Automatic segmentation of seven retinal layers in SDOCT images congruent with expert manual segmentation,” Opt. Express 18(18), 19413–19428 (2010).
[Crossref] [PubMed]

Ferencz, M.

D. C. DeBuc, G. M. Somfai, S. Ranganathan, E. Tátrai, M. Ferencz, and C. A. Puliafito, “Reliability and reproducibility of macular segmentation using a custom-built optical coherence tomography retinal image analysis software,” J. Biomed. Opt. 14(6), 064023 (2009).
[Crossref] [PubMed]

Fernández, D. C.

D. C. Fernández, “Delineating Fluid-Filled Region Boundaries in Optical Coherence Tomography Images of the Retina,” IEEE Trans. Med. Imaging 24(8), 929–945 (2005).
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Feuer, W. J.

G. Gregori, F. Wang, P. J. Rosenfeld, Z. Yehoshua, N. Z. Gregori, B. J. Lujan, C. A. Puliafito, and W. J. Feuer, “Spectral domain optical coherence tomography imaging of drusen in nonexudative age-related macular degeneration,” Ophthalmology 118(7), 1373–1379 (2011).
[PubMed]

Foi, A.

K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering,” IEEE Trans. Image Process. 16(8), 2080–2095 (2007).
[Crossref] [PubMed]

Folgar, F. A.

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, and C. A. Toth, “Quantitative Classification of Eyes with and without Intermediate Age-related Macular Degeneration Using Optical Coherence Tomography,” Ophthalmology 121(1), 162–172 (2014).

Fujimoto, J. G.

Y.-Y. Liu, H. Ishikawa, M. Chen, G. Wollstein, J. S. Duker, J. G. Fujimoto, J. S. Schuman, and J. M. Rehg, “Computerized macular pathology diagnosis in spectral domain optical coherence tomography scans based on multiscale texture and shape features,” Invest. Ophthalmol. Vis. Sci. 52(11), 8316–8322 (2011).
[Crossref] [PubMed]

H. Ishikawa, D. M. Stein, G. Wollstein, S. Beaton, J. G. Fujimoto, and J. S. Schuman, “Macular Segmentation with Optical Coherence Tomography,” Invest. Ophthalmol. Vis. Sci. 46(6), 2012–2017 (2005).
[Crossref] [PubMed]

L. A. Paunescu, J. S. Schuman, L. L. Price, P. C. Stark, S. Beaton, H. Ishikawa, G. Wollstein, and J. G. Fujimoto, “Reproducibility of Nerve Fiber Thickness, Macular Thickness, and Optic Nerve Head Measurements Using StratusOCT,” Invest. Ophthalmol. Vis. Sci. 45(6), 1716–1724 (2004).
[Crossref] [PubMed]

M. R. Hee, J. A. Izatt, E. A. Swanson, D. Huang, J. S. Schuman, C. P. Lin, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography of the human retina,” Arch. Ophthalmol. 113(3), 325–332 (1995).
[Crossref] [PubMed]

Garvin, M. K.

Grant, M. B.

J. Yellowlees Douglas, A. D. Bhatwadekar, S. Li Calzi, L. C. Shaw, D. Carnegie, S. Caballero, Q. Li, A. W. Stitt, M. K. Raizada, and M. B. Grant, “Bone marrow-CNS connections: Implications in the pathogenesis of diabetic retinopathy,” Prog. Retin. Eye Res. 31(5), 481–494 (2012).
[Crossref] [PubMed]

Gregori, G.

G. Gregori, F. Wang, P. J. Rosenfeld, Z. Yehoshua, N. Z. Gregori, B. J. Lujan, C. A. Puliafito, and W. J. Feuer, “Spectral domain optical coherence tomography imaging of drusen in nonexudative age-related macular degeneration,” Ophthalmology 118(7), 1373–1379 (2011).
[PubMed]

Gregori, N. Z.

G. Gregori, F. Wang, P. J. Rosenfeld, Z. Yehoshua, N. Z. Gregori, B. J. Lujan, C. A. Puliafito, and W. J. Feuer, “Spectral domain optical coherence tomography imaging of drusen in nonexudative age-related macular degeneration,” Ophthalmology 118(7), 1373–1379 (2011).
[PubMed]

Harper, M. M.

Hauser, M.

Hee, M. R.

M. R. Hee, J. A. Izatt, E. A. Swanson, D. Huang, J. S. Schuman, C. P. Lin, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography of the human retina,” Arch. Ophthalmol. 113(3), 325–332 (1995).
[Crossref] [PubMed]

Heflin, S. J.

Hood, D. C.

Hornegger, J.

Huang, D.

O. Tan, G. Li, A. T.-H. Lu, R. Varma, and D. Huang, “Mapping of Macular Substructures with Optical Coherence Tomography for Glaucoma Diagnosis,” Ophthalmology 115(6), 949–956 (2008).

M. R. Hee, J. A. Izatt, E. A. Swanson, D. Huang, J. S. Schuman, C. P. Lin, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography of the human retina,” Arch. Ophthalmol. 113(3), 325–332 (1995).
[Crossref] [PubMed]

Ishikawa, H.

Y.-Y. Liu, H. Ishikawa, M. Chen, G. Wollstein, J. S. Duker, J. G. Fujimoto, J. S. Schuman, and J. M. Rehg, “Computerized macular pathology diagnosis in spectral domain optical coherence tomography scans based on multiscale texture and shape features,” Invest. Ophthalmol. Vis. Sci. 52(11), 8316–8322 (2011).
[Crossref] [PubMed]

H. Ishikawa, D. M. Stein, G. Wollstein, S. Beaton, J. G. Fujimoto, and J. S. Schuman, “Macular Segmentation with Optical Coherence Tomography,” Invest. Ophthalmol. Vis. Sci. 46(6), 2012–2017 (2005).
[Crossref] [PubMed]

L. A. Paunescu, J. S. Schuman, L. L. Price, P. C. Stark, S. Beaton, H. Ishikawa, G. Wollstein, and J. G. Fujimoto, “Reproducibility of Nerve Fiber Thickness, Macular Thickness, and Optic Nerve Head Measurements Using StratusOCT,” Invest. Ophthalmol. Vis. Sci. 45(6), 1716–1724 (2004).
[Crossref] [PubMed]

Izatt, J. A.

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, and C. A. Toth, “Quantitative Classification of Eyes with and without Intermediate Age-related Macular Degeneration Using Optical Coherence Tomography,” Ophthalmology 121(1), 162–172 (2014).

P. P. Srinivasan, S. J. Heflin, J. A. Izatt, V. Y. Arshavsky, and S. Farsiu, “Automatic segmentation of up to ten layer boundaries in SD-OCT images of the mouse retina with and without missing layers due to pathology,” Biomed. Opt. Express 5(2), 348–365 (2014).
[Crossref] [PubMed]

A. N. Kuo, R. P. McNabb, S. J. Chiu, M. A. El-Dairi, S. Farsiu, C. A. Toth, and J. A. Izatt, “Correction of Ocular Shape in Retinal Optical Coherence Tomography and Effect on Current Clinical Measures,” Am. J. Ophthalmol. 156(2), 304–311 (2013).
[Crossref] [PubMed]

J. Y. Lee, S. J. Chiu, P. Srinivasan, J. A. Izatt, C. A. Toth, S. Farsiu, and G. J. Jaffe, “Fully Automatic Software for Quantification of Retinal Thickness and Volume in Eyes with Diabetic Macular Edema from Images Acquired by Cirrus and Spectralis Spectral Domain Optical Coherence Tomography Machines,” Invest. Ophthalmol. Vis. Sci. 54, 7595–7602 (2013).
[Crossref] [PubMed]

S. J. Chiu, J. A. Izatt, R. V. O’Connell, K. P. Winter, C. A. Toth, and S. Farsiu, “Validated Automatic Segmentation of AMD Pathology Including Drusen and Geographic Atrophy in SD-OCT Images,” Invest. Ophthalmol. Vis. Sci. 53(1), 53–61 (2012).
[Crossref] [PubMed]

L. Fang, S. Li, Q. Nie, J. A. Izatt, C. A. Toth, and S. Farsiu, “Sparsity based denoising of spectral domain optical coherence tomography images,” Biomed. Opt. Express 3(5), 927–942 (2012).
[Crossref] [PubMed]

S. J. Chiu, C. A. Toth, C. Bowes Rickman, J. A. Izatt, and S. Farsiu, “Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming,” Biomed. Opt. Express 3(5), 1127–1140 (2012).
[Crossref] [PubMed]

S. J. Chiu, X. T. Li, P. Nicholas, C. A. Toth, J. A. Izatt, and S. Farsiu, “Automatic segmentation of seven retinal layers in SDOCT images congruent with expert manual segmentation,” Opt. Express 18(18), 19413–19428 (2010).
[Crossref] [PubMed]

M. R. Hee, J. A. Izatt, E. A. Swanson, D. Huang, J. S. Schuman, C. P. Lin, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography of the human retina,” Arch. Ophthalmol. 113(3), 325–332 (1995).
[Crossref] [PubMed]

Jaffe, G. J.

J. Y. Lee, S. J. Chiu, P. Srinivasan, J. A. Izatt, C. A. Toth, S. Farsiu, and G. J. Jaffe, “Fully Automatic Software for Quantification of Retinal Thickness and Volume in Eyes with Diabetic Macular Edema from Images Acquired by Cirrus and Spectralis Spectral Domain Optical Coherence Tomography Machines,” Invest. Ophthalmol. Vis. Sci. 54, 7595–7602 (2013).
[Crossref] [PubMed]

Jeong, W.

Jiang, H.

G. M. Somfai, E. Tátrai, L. Laurik, B. Varga, V. Ölvedy, H. Jiang, J. Wang, W. E. Smiddy, A. Somogyi, and D. C. DeBuc, “Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes,” BMC Bioinformatics 15(1), 106 (2014).
[Crossref] [PubMed]

Joo, C.

Kardon, R.

Katkovnik, V.

K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering,” IEEE Trans. Image Process. 16(8), 2080–2095 (2007).
[Crossref] [PubMed]

Klingeborn, M.

C. Bowes Rickman, S. Farsiu, C. A. Toth, and M. Klingeborn, “Dry Age-Related Macular Degeneration: Mechanisms, Therapeutic Targets, and Imaging,” Invest. Ophthalmol. Vis. Sci. 54(14), ORSF68 (2013).
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Koprowski, R.

R. Koprowski, S. Teper, Z. Wróbel, and E. Wylegala, “Automatic analysis of selected choroidal diseases in OCT images of the eye fundus,” Biomed. Eng. Online 12(1), 117 (2013).
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Kuo, A. N.

A. N. Kuo, R. P. McNabb, S. J. Chiu, M. A. El-Dairi, S. Farsiu, C. A. Toth, and J. A. Izatt, “Correction of Ocular Shape in Retinal Optical Coherence Tomography and Effect on Current Clinical Measures,” Am. J. Ophthalmol. 156(2), 304–311 (2013).
[Crossref] [PubMed]

Kwon, Y. H.

Lang, A.

Laurik, L.

G. M. Somfai, E. Tátrai, L. Laurik, B. Varga, V. Ölvedy, H. Jiang, J. Wang, W. E. Smiddy, A. Somogyi, and D. C. DeBuc, “Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes,” BMC Bioinformatics 15(1), 106 (2014).
[Crossref] [PubMed]

Lee, J. Y.

J. Y. Lee, S. J. Chiu, P. Srinivasan, J. A. Izatt, C. A. Toth, S. Farsiu, and G. J. Jaffe, “Fully Automatic Software for Quantification of Retinal Thickness and Volume in Eyes with Diabetic Macular Edema from Images Acquired by Cirrus and Spectralis Spectral Domain Optical Coherence Tomography Machines,” Invest. Ophthalmol. Vis. Sci. 54, 7595–7602 (2013).
[Crossref] [PubMed]

Lemij, H. G.

Li, G.

O. Tan, G. Li, A. T.-H. Lu, R. Varma, and D. Huang, “Mapping of Macular Substructures with Optical Coherence Tomography for Glaucoma Diagnosis,” Ophthalmology 115(6), 949–956 (2008).

Li, Q.

J. Yellowlees Douglas, A. D. Bhatwadekar, S. Li Calzi, L. C. Shaw, D. Carnegie, S. Caballero, Q. Li, A. W. Stitt, M. K. Raizada, and M. B. Grant, “Bone marrow-CNS connections: Implications in the pathogenesis of diabetic retinopathy,” Prog. Retin. Eye Res. 31(5), 481–494 (2012).
[Crossref] [PubMed]

Li, S.

Li, X. T.

Li Calzi, S.

J. Yellowlees Douglas, A. D. Bhatwadekar, S. Li Calzi, L. C. Shaw, D. Carnegie, S. Caballero, Q. Li, A. W. Stitt, M. K. Raizada, and M. B. Grant, “Bone marrow-CNS connections: Implications in the pathogenesis of diabetic retinopathy,” Prog. Retin. Eye Res. 31(5), 481–494 (2012).
[Crossref] [PubMed]

Lin, C. P.

M. R. Hee, J. A. Izatt, E. A. Swanson, D. Huang, J. S. Schuman, C. P. Lin, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography of the human retina,” Arch. Ophthalmol. 113(3), 325–332 (1995).
[Crossref] [PubMed]

Liu, Y.-Y.

Y.-Y. Liu, H. Ishikawa, M. Chen, G. Wollstein, J. S. Duker, J. G. Fujimoto, J. S. Schuman, and J. M. Rehg, “Computerized macular pathology diagnosis in spectral domain optical coherence tomography scans based on multiscale texture and shape features,” Invest. Ophthalmol. Vis. Sci. 52(11), 8316–8322 (2011).
[Crossref] [PubMed]

Lu, A. T.-H.

O. Tan, G. Li, A. T.-H. Lu, R. Varma, and D. Huang, “Mapping of Macular Substructures with Optical Coherence Tomography for Glaucoma Diagnosis,” Ophthalmology 115(6), 949–956 (2008).

Lu, W.

Y. Zhang, B. Zhang, F. Coenen, J. Xiao, and W. Lu, “One-class kernel subspace ensemble for medical image classification,” EURASIP J. Adv. Signal Process. 2014, 1–13 (2014).

Lujan, B. J.

G. Gregori, F. Wang, P. J. Rosenfeld, Z. Yehoshua, N. Z. Gregori, B. J. Lujan, C. A. Puliafito, and W. J. Feuer, “Spectral domain optical coherence tomography imaging of drusen in nonexudative age-related macular degeneration,” Ophthalmology 118(7), 1373–1379 (2011).
[PubMed]

Mardin, C. Y.

Mayer, M. A.

McNabb, R. P.

A. N. Kuo, R. P. McNabb, S. J. Chiu, M. A. El-Dairi, S. Farsiu, C. A. Toth, and J. A. Izatt, “Correction of Ocular Shape in Retinal Optical Coherence Tomography and Effect on Current Clinical Measures,” Am. J. Ophthalmol. 156(2), 304–311 (2013).
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Medeiros, F. A.

F. A. Medeiros, L. M. Zangwill, C. Bowd, R. M. Vessani, R. Susanna, and R. N. Weinreb, “Evaluation of retinal nerve fiber layer, optic nerve head, and macular thickness measurements for glaucoma detection using optical coherence tomography,” Am. J. Ophthalmol. 139(1), 44–55 (2005).
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Mishra, A.

Mujat, M.

Nicholas, P.

Nie, Q.

O’Connell, R. V.

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, and C. A. Toth, “Quantitative Classification of Eyes with and without Intermediate Age-related Macular Degeneration Using Optical Coherence Tomography,” Ophthalmology 121(1), 162–172 (2014).

S. J. Chiu, J. A. Izatt, R. V. O’Connell, K. P. Winter, C. A. Toth, and S. Farsiu, “Validated Automatic Segmentation of AMD Pathology Including Drusen and Geographic Atrophy in SD-OCT Images,” Invest. Ophthalmol. Vis. Sci. 53(1), 53–61 (2012).
[Crossref] [PubMed]

Ölvedy, V.

G. M. Somfai, E. Tátrai, L. Laurik, B. Varga, V. Ölvedy, H. Jiang, J. Wang, W. E. Smiddy, A. Somogyi, and D. C. DeBuc, “Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes,” BMC Bioinformatics 15(1), 106 (2014).
[Crossref] [PubMed]

Park, B.

Paunescu, L. A.

L. A. Paunescu, J. S. Schuman, L. L. Price, P. C. Stark, S. Beaton, H. Ishikawa, G. Wollstein, and J. G. Fujimoto, “Reproducibility of Nerve Fiber Thickness, Macular Thickness, and Optic Nerve Head Measurements Using StratusOCT,” Invest. Ophthalmol. Vis. Sci. 45(6), 1716–1724 (2004).
[Crossref] [PubMed]

Price, L. L.

L. A. Paunescu, J. S. Schuman, L. L. Price, P. C. Stark, S. Beaton, H. Ishikawa, G. Wollstein, and J. G. Fujimoto, “Reproducibility of Nerve Fiber Thickness, Macular Thickness, and Optic Nerve Head Measurements Using StratusOCT,” Invest. Ophthalmol. Vis. Sci. 45(6), 1716–1724 (2004).
[Crossref] [PubMed]

Prince, J. L.

Puliafito, C. A.

G. Gregori, F. Wang, P. J. Rosenfeld, Z. Yehoshua, N. Z. Gregori, B. J. Lujan, C. A. Puliafito, and W. J. Feuer, “Spectral domain optical coherence tomography imaging of drusen in nonexudative age-related macular degeneration,” Ophthalmology 118(7), 1373–1379 (2011).
[PubMed]

D. C. DeBuc, G. M. Somfai, S. Ranganathan, E. Tátrai, M. Ferencz, and C. A. Puliafito, “Reliability and reproducibility of macular segmentation using a custom-built optical coherence tomography retinal image analysis software,” J. Biomed. Opt. 14(6), 064023 (2009).
[Crossref] [PubMed]

D. Cabrera Fernández, H. M. Salinas, and C. A. Puliafito, “Automated detection of retinal layer structures on optical coherence tomography images,” Opt. Express 13(25), 10200–10216 (2005).
[Crossref] [PubMed]

M. R. Hee, J. A. Izatt, E. A. Swanson, D. Huang, J. S. Schuman, C. P. Lin, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography of the human retina,” Arch. Ophthalmol. 113(3), 325–332 (1995).
[Crossref] [PubMed]

Raizada, M. K.

J. Yellowlees Douglas, A. D. Bhatwadekar, S. Li Calzi, L. C. Shaw, D. Carnegie, S. Caballero, Q. Li, A. W. Stitt, M. K. Raizada, and M. B. Grant, “Bone marrow-CNS connections: Implications in the pathogenesis of diabetic retinopathy,” Prog. Retin. Eye Res. 31(5), 481–494 (2012).
[Crossref] [PubMed]

Ramachandran, R.

Ranganathan, S.

D. C. DeBuc, G. M. Somfai, S. Ranganathan, E. Tátrai, M. Ferencz, and C. A. Puliafito, “Reliability and reproducibility of macular segmentation using a custom-built optical coherence tomography retinal image analysis software,” J. Biomed. Opt. 14(6), 064023 (2009).
[Crossref] [PubMed]

Raza, A.

Rehg, J. M.

Y.-Y. Liu, H. Ishikawa, M. Chen, G. Wollstein, J. S. Duker, J. G. Fujimoto, J. S. Schuman, and J. M. Rehg, “Computerized macular pathology diagnosis in spectral domain optical coherence tomography scans based on multiscale texture and shape features,” Invest. Ophthalmol. Vis. Sci. 52(11), 8316–8322 (2011).
[Crossref] [PubMed]

Reisman, C. A.

Rosenfeld, P. J.

G. Gregori, F. Wang, P. J. Rosenfeld, Z. Yehoshua, N. Z. Gregori, B. J. Lujan, C. A. Puliafito, and W. J. Feuer, “Spectral domain optical coherence tomography imaging of drusen in nonexudative age-related macular degeneration,” Ophthalmology 118(7), 1373–1379 (2011).
[PubMed]

Salinas, H. M.

Schuman, J. S.

Y.-Y. Liu, H. Ishikawa, M. Chen, G. Wollstein, J. S. Duker, J. G. Fujimoto, J. S. Schuman, and J. M. Rehg, “Computerized macular pathology diagnosis in spectral domain optical coherence tomography scans based on multiscale texture and shape features,” Invest. Ophthalmol. Vis. Sci. 52(11), 8316–8322 (2011).
[Crossref] [PubMed]

H. Ishikawa, D. M. Stein, G. Wollstein, S. Beaton, J. G. Fujimoto, and J. S. Schuman, “Macular Segmentation with Optical Coherence Tomography,” Invest. Ophthalmol. Vis. Sci. 46(6), 2012–2017 (2005).
[Crossref] [PubMed]

L. A. Paunescu, J. S. Schuman, L. L. Price, P. C. Stark, S. Beaton, H. Ishikawa, G. Wollstein, and J. G. Fujimoto, “Reproducibility of Nerve Fiber Thickness, Macular Thickness, and Optic Nerve Head Measurements Using StratusOCT,” Invest. Ophthalmol. Vis. Sci. 45(6), 1716–1724 (2004).
[Crossref] [PubMed]

M. R. Hee, J. A. Izatt, E. A. Swanson, D. Huang, J. S. Schuman, C. P. Lin, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography of the human retina,” Arch. Ophthalmol. 113(3), 325–332 (1995).
[Crossref] [PubMed]

Shahidi, M.

M. Shahidi, Z. Wang, and R. Zelkha, “Quantitative Thickness Measurement of Retinal Layers Imaged by Optical Coherence Tomography,” Am. J. Ophthalmol. 139(6), 1056–1061 (2005).
[Crossref] [PubMed]

Shaw, L. C.

J. Yellowlees Douglas, A. D. Bhatwadekar, S. Li Calzi, L. C. Shaw, D. Carnegie, S. Caballero, Q. Li, A. W. Stitt, M. K. Raizada, and M. B. Grant, “Bone marrow-CNS connections: Implications in the pathogenesis of diabetic retinopathy,” Prog. Retin. Eye Res. 31(5), 481–494 (2012).
[Crossref] [PubMed]

Smiddy, W. E.

G. M. Somfai, E. Tátrai, L. Laurik, B. Varga, V. Ölvedy, H. Jiang, J. Wang, W. E. Smiddy, A. Somogyi, and D. C. DeBuc, “Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes,” BMC Bioinformatics 15(1), 106 (2014).
[Crossref] [PubMed]

Sohn, E. H.

Somfai, G. M.

G. M. Somfai, E. Tátrai, L. Laurik, B. Varga, V. Ölvedy, H. Jiang, J. Wang, W. E. Smiddy, A. Somogyi, and D. C. DeBuc, “Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes,” BMC Bioinformatics 15(1), 106 (2014).
[Crossref] [PubMed]

D. C. DeBuc, G. M. Somfai, S. Ranganathan, E. Tátrai, M. Ferencz, and C. A. Puliafito, “Reliability and reproducibility of macular segmentation using a custom-built optical coherence tomography retinal image analysis software,” J. Biomed. Opt. 14(6), 064023 (2009).
[Crossref] [PubMed]

Somogyi, A.

G. M. Somfai, E. Tátrai, L. Laurik, B. Varga, V. Ölvedy, H. Jiang, J. Wang, W. E. Smiddy, A. Somogyi, and D. C. DeBuc, “Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes,” BMC Bioinformatics 15(1), 106 (2014).
[Crossref] [PubMed]

Sotirchos, E. S.

Srinivasan, P.

J. Y. Lee, S. J. Chiu, P. Srinivasan, J. A. Izatt, C. A. Toth, S. Farsiu, and G. J. Jaffe, “Fully Automatic Software for Quantification of Retinal Thickness and Volume in Eyes with Diabetic Macular Edema from Images Acquired by Cirrus and Spectralis Spectral Domain Optical Coherence Tomography Machines,” Invest. Ophthalmol. Vis. Sci. 54, 7595–7602 (2013).
[Crossref] [PubMed]

Srinivasan, P. P.

Stark, P. C.

L. A. Paunescu, J. S. Schuman, L. L. Price, P. C. Stark, S. Beaton, H. Ishikawa, G. Wollstein, and J. G. Fujimoto, “Reproducibility of Nerve Fiber Thickness, Macular Thickness, and Optic Nerve Head Measurements Using StratusOCT,” Invest. Ophthalmol. Vis. Sci. 45(6), 1716–1724 (2004).
[Crossref] [PubMed]

Stein, D. M.

H. Ishikawa, D. M. Stein, G. Wollstein, S. Beaton, J. G. Fujimoto, and J. S. Schuman, “Macular Segmentation with Optical Coherence Tomography,” Invest. Ophthalmol. Vis. Sci. 46(6), 2012–2017 (2005).
[Crossref] [PubMed]

Stitt, A. W.

J. Yellowlees Douglas, A. D. Bhatwadekar, S. Li Calzi, L. C. Shaw, D. Carnegie, S. Caballero, Q. Li, A. W. Stitt, M. K. Raizada, and M. B. Grant, “Bone marrow-CNS connections: Implications in the pathogenesis of diabetic retinopathy,” Prog. Retin. Eye Res. 31(5), 481–494 (2012).
[Crossref] [PubMed]

Susanna, R.

F. A. Medeiros, L. M. Zangwill, C. Bowd, R. M. Vessani, R. Susanna, and R. N. Weinreb, “Evaluation of retinal nerve fiber layer, optic nerve head, and macular thickness measurements for glaucoma detection using optical coherence tomography,” Am. J. Ophthalmol. 139(1), 44–55 (2005).
[Crossref] [PubMed]

Swanson, E. A.

M. R. Hee, J. A. Izatt, E. A. Swanson, D. Huang, J. S. Schuman, C. P. Lin, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography of the human retina,” Arch. Ophthalmol. 113(3), 325–332 (1995).
[Crossref] [PubMed]

Tan, O.

O. Tan, G. Li, A. T.-H. Lu, R. Varma, and D. Huang, “Mapping of Macular Substructures with Optical Coherence Tomography for Glaucoma Diagnosis,” Ophthalmology 115(6), 949–956 (2008).

Tátrai, E.

G. M. Somfai, E. Tátrai, L. Laurik, B. Varga, V. Ölvedy, H. Jiang, J. Wang, W. E. Smiddy, A. Somogyi, and D. C. DeBuc, “Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes,” BMC Bioinformatics 15(1), 106 (2014).
[Crossref] [PubMed]

D. C. DeBuc, G. M. Somfai, S. Ranganathan, E. Tátrai, M. Ferencz, and C. A. Puliafito, “Reliability and reproducibility of macular segmentation using a custom-built optical coherence tomography retinal image analysis software,” J. Biomed. Opt. 14(6), 064023 (2009).
[Crossref] [PubMed]

Teper, S.

R. Koprowski, S. Teper, Z. Wróbel, and E. Wylegala, “Automatic analysis of selected choroidal diseases in OCT images of the eye fundus,” Biomed. Eng. Online 12(1), 117 (2013).
[Crossref] [PubMed]

Tornow, R. P.

Toth, C. A.

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, and C. A. Toth, “Quantitative Classification of Eyes with and without Intermediate Age-related Macular Degeneration Using Optical Coherence Tomography,” Ophthalmology 121(1), 162–172 (2014).

C. Bowes Rickman, S. Farsiu, C. A. Toth, and M. Klingeborn, “Dry Age-Related Macular Degeneration: Mechanisms, Therapeutic Targets, and Imaging,” Invest. Ophthalmol. Vis. Sci. 54(14), ORSF68 (2013).
[Crossref] [PubMed]

J. Y. Lee, S. J. Chiu, P. Srinivasan, J. A. Izatt, C. A. Toth, S. Farsiu, and G. J. Jaffe, “Fully Automatic Software for Quantification of Retinal Thickness and Volume in Eyes with Diabetic Macular Edema from Images Acquired by Cirrus and Spectralis Spectral Domain Optical Coherence Tomography Machines,” Invest. Ophthalmol. Vis. Sci. 54, 7595–7602 (2013).
[Crossref] [PubMed]

A. N. Kuo, R. P. McNabb, S. J. Chiu, M. A. El-Dairi, S. Farsiu, C. A. Toth, and J. A. Izatt, “Correction of Ocular Shape in Retinal Optical Coherence Tomography and Effect on Current Clinical Measures,” Am. J. Ophthalmol. 156(2), 304–311 (2013).
[Crossref] [PubMed]

S. J. Chiu, J. A. Izatt, R. V. O’Connell, K. P. Winter, C. A. Toth, and S. Farsiu, “Validated Automatic Segmentation of AMD Pathology Including Drusen and Geographic Atrophy in SD-OCT Images,” Invest. Ophthalmol. Vis. Sci. 53(1), 53–61 (2012).
[Crossref] [PubMed]

L. Fang, S. Li, Q. Nie, J. A. Izatt, C. A. Toth, and S. Farsiu, “Sparsity based denoising of spectral domain optical coherence tomography images,” Biomed. Opt. Express 3(5), 927–942 (2012).
[Crossref] [PubMed]

S. J. Chiu, C. A. Toth, C. Bowes Rickman, J. A. Izatt, and S. Farsiu, “Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming,” Biomed. Opt. Express 3(5), 1127–1140 (2012).
[Crossref] [PubMed]

S. J. Chiu, X. T. Li, P. Nicholas, C. A. Toth, J. A. Izatt, and S. Farsiu, “Automatic segmentation of seven retinal layers in SDOCT images congruent with expert manual segmentation,” Opt. Express 18(18), 19413–19428 (2010).
[Crossref] [PubMed]

van der Schoot, J.

Vapnik, V.

C. Cortes and V. Vapnik, “Support-vector networks,” Mach. Learn. 20(3), 273–297 (1995).
[Crossref]

Varga, B.

G. M. Somfai, E. Tátrai, L. Laurik, B. Varga, V. Ölvedy, H. Jiang, J. Wang, W. E. Smiddy, A. Somogyi, and D. C. DeBuc, “Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes,” BMC Bioinformatics 15(1), 106 (2014).
[Crossref] [PubMed]

Varma, R.

O. Tan, G. Li, A. T.-H. Lu, R. Varma, and D. Huang, “Mapping of Macular Substructures with Optical Coherence Tomography for Glaucoma Diagnosis,” Ophthalmology 115(6), 949–956 (2008).

Vermeer, K. A.

Vessani, R. M.

F. A. Medeiros, L. M. Zangwill, C. Bowd, R. M. Vessani, R. Susanna, and R. N. Weinreb, “Evaluation of retinal nerve fiber layer, optic nerve head, and macular thickness measurements for glaucoma detection using optical coherence tomography,” Am. J. Ophthalmol. 139(1), 44–55 (2005).
[Crossref] [PubMed]

Wagner, M.

Wang, F.

G. Gregori, F. Wang, P. J. Rosenfeld, Z. Yehoshua, N. Z. Gregori, B. J. Lujan, C. A. Puliafito, and W. J. Feuer, “Spectral domain optical coherence tomography imaging of drusen in nonexudative age-related macular degeneration,” Ophthalmology 118(7), 1373–1379 (2011).
[PubMed]

Wang, J.

G. M. Somfai, E. Tátrai, L. Laurik, B. Varga, V. Ölvedy, H. Jiang, J. Wang, W. E. Smiddy, A. Somogyi, and D. C. DeBuc, “Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes,” BMC Bioinformatics 15(1), 106 (2014).
[Crossref] [PubMed]

Wang, Z.

M. Shahidi, Z. Wang, and R. Zelkha, “Quantitative Thickness Measurement of Retinal Layers Imaged by Optical Coherence Tomography,” Am. J. Ophthalmol. 139(6), 1056–1061 (2005).
[Crossref] [PubMed]

Weinreb, R. N.

F. A. Medeiros, L. M. Zangwill, C. Bowd, R. M. Vessani, R. Susanna, and R. N. Weinreb, “Evaluation of retinal nerve fiber layer, optic nerve head, and macular thickness measurements for glaucoma detection using optical coherence tomography,” Am. J. Ophthalmol. 139(1), 44–55 (2005).
[Crossref] [PubMed]

Winter, K. P.

S. J. Chiu, J. A. Izatt, R. V. O’Connell, K. P. Winter, C. A. Toth, and S. Farsiu, “Validated Automatic Segmentation of AMD Pathology Including Drusen and Geographic Atrophy in SD-OCT Images,” Invest. Ophthalmol. Vis. Sci. 53(1), 53–61 (2012).
[Crossref] [PubMed]

Wollstein, G.

Y.-Y. Liu, H. Ishikawa, M. Chen, G. Wollstein, J. S. Duker, J. G. Fujimoto, J. S. Schuman, and J. M. Rehg, “Computerized macular pathology diagnosis in spectral domain optical coherence tomography scans based on multiscale texture and shape features,” Invest. Ophthalmol. Vis. Sci. 52(11), 8316–8322 (2011).
[Crossref] [PubMed]

H. Ishikawa, D. M. Stein, G. Wollstein, S. Beaton, J. G. Fujimoto, and J. S. Schuman, “Macular Segmentation with Optical Coherence Tomography,” Invest. Ophthalmol. Vis. Sci. 46(6), 2012–2017 (2005).
[Crossref] [PubMed]

L. A. Paunescu, J. S. Schuman, L. L. Price, P. C. Stark, S. Beaton, H. Ishikawa, G. Wollstein, and J. G. Fujimoto, “Reproducibility of Nerve Fiber Thickness, Macular Thickness, and Optic Nerve Head Measurements Using StratusOCT,” Invest. Ophthalmol. Vis. Sci. 45(6), 1716–1724 (2004).
[Crossref] [PubMed]

Wong, A.

Wróbel, Z.

R. Koprowski, S. Teper, Z. Wróbel, and E. Wylegala, “Automatic analysis of selected choroidal diseases in OCT images of the eye fundus,” Biomed. Eng. Online 12(1), 117 (2013).
[Crossref] [PubMed]

Wylegala, E.

R. Koprowski, S. Teper, Z. Wróbel, and E. Wylegala, “Automatic analysis of selected choroidal diseases in OCT images of the eye fundus,” Biomed. Eng. Online 12(1), 117 (2013).
[Crossref] [PubMed]

Xiao, J.

Y. Zhang, B. Zhang, F. Coenen, J. Xiao, and W. Lu, “One-class kernel subspace ensemble for medical image classification,” EURASIP J. Adv. Signal Process. 2014, 1–13 (2014).

Yang, Q.

Yehoshua, Z.

G. Gregori, F. Wang, P. J. Rosenfeld, Z. Yehoshua, N. Z. Gregori, B. J. Lujan, C. A. Puliafito, and W. J. Feuer, “Spectral domain optical coherence tomography imaging of drusen in nonexudative age-related macular degeneration,” Ophthalmology 118(7), 1373–1379 (2011).
[PubMed]

Yellowlees Douglas, J.

J. Yellowlees Douglas, A. D. Bhatwadekar, S. Li Calzi, L. C. Shaw, D. Carnegie, S. Caballero, Q. Li, A. W. Stitt, M. K. Raizada, and M. B. Grant, “Bone marrow-CNS connections: Implications in the pathogenesis of diabetic retinopathy,” Prog. Retin. Eye Res. 31(5), 481–494 (2012).
[Crossref] [PubMed]

Ying, H. S.

Yuan, E.

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, and C. A. Toth, “Quantitative Classification of Eyes with and without Intermediate Age-related Macular Degeneration Using Optical Coherence Tomography,” Ophthalmology 121(1), 162–172 (2014).

Zangwill, L. M.

F. A. Medeiros, L. M. Zangwill, C. Bowd, R. M. Vessani, R. Susanna, and R. N. Weinreb, “Evaluation of retinal nerve fiber layer, optic nerve head, and macular thickness measurements for glaucoma detection using optical coherence tomography,” Am. J. Ophthalmol. 139(1), 44–55 (2005).
[Crossref] [PubMed]

Zelkha, R.

M. Shahidi, Z. Wang, and R. Zelkha, “Quantitative Thickness Measurement of Retinal Layers Imaged by Optical Coherence Tomography,” Am. J. Ophthalmol. 139(6), 1056–1061 (2005).
[Crossref] [PubMed]

Zhang, B.

Y. Zhang, B. Zhang, F. Coenen, J. Xiao, and W. Lu, “One-class kernel subspace ensemble for medical image classification,” EURASIP J. Adv. Signal Process. 2014, 1–13 (2014).

Zhang, Y.

Y. Zhang, B. Zhang, F. Coenen, J. Xiao, and W. Lu, “One-class kernel subspace ensemble for medical image classification,” EURASIP J. Adv. Signal Process. 2014, 1–13 (2014).

Am. J. Ophthalmol. (3)

M. Shahidi, Z. Wang, and R. Zelkha, “Quantitative Thickness Measurement of Retinal Layers Imaged by Optical Coherence Tomography,” Am. J. Ophthalmol. 139(6), 1056–1061 (2005).
[Crossref] [PubMed]

F. A. Medeiros, L. M. Zangwill, C. Bowd, R. M. Vessani, R. Susanna, and R. N. Weinreb, “Evaluation of retinal nerve fiber layer, optic nerve head, and macular thickness measurements for glaucoma detection using optical coherence tomography,” Am. J. Ophthalmol. 139(1), 44–55 (2005).
[Crossref] [PubMed]

A. N. Kuo, R. P. McNabb, S. J. Chiu, M. A. El-Dairi, S. Farsiu, C. A. Toth, and J. A. Izatt, “Correction of Ocular Shape in Retinal Optical Coherence Tomography and Effect on Current Clinical Measures,” Am. J. Ophthalmol. 156(2), 304–311 (2013).
[Crossref] [PubMed]

Arch. Ophthalmol. (2)

Age-Related Eye Disease Study Research Group, “A randomized, placebo-controlled, clinical trial of high-dose supplementation with vitamins C and E, beta carotene, and zinc for age-related macular degeneration and vision loss: AREDS report no. 8,” Arch. Ophthalmol. 119(10), 1417–1436 (2001).
[Crossref] [PubMed]

M. R. Hee, J. A. Izatt, E. A. Swanson, D. Huang, J. S. Schuman, C. P. Lin, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography of the human retina,” Arch. Ophthalmol. 113(3), 325–332 (1995).
[Crossref] [PubMed]

Biomed. Eng. Online (1)

R. Koprowski, S. Teper, Z. Wróbel, and E. Wylegala, “Automatic analysis of selected choroidal diseases in OCT images of the eye fundus,” Biomed. Eng. Online 12(1), 117 (2013).
[Crossref] [PubMed]

Biomed. Opt. Express (10)

S. J. Chiu, C. A. Toth, C. Bowes Rickman, J. A. Izatt, and S. Farsiu, “Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming,” Biomed. Opt. Express 3(5), 1127–1140 (2012).
[Crossref] [PubMed]

P. P. Srinivasan, S. J. Heflin, J. A. Izatt, V. Y. Arshavsky, and S. Farsiu, “Automatic segmentation of up to ten layer boundaries in SD-OCT images of the mouse retina with and without missing layers due to pathology,” Biomed. Opt. Express 5(2), 348–365 (2014).
[Crossref] [PubMed]

L. Fang, S. Li, Q. Nie, J. A. Izatt, C. A. Toth, and S. Farsiu, “Sparsity based denoising of spectral domain optical coherence tomography images,” Biomed. Opt. Express 3(5), 927–942 (2012).
[Crossref] [PubMed]

M. A. Mayer, A. Borsdorf, M. Wagner, J. Hornegger, C. Y. Mardin, and R. P. Tornow, “Wavelet denoising of multiframe optical coherence tomography data,” Biomed. Opt. Express 3(3), 572–589 (2012).
[Crossref] [PubMed]

B. J. Antony, M. D. Abràmoff, M. M. Harper, W. Jeong, E. H. Sohn, Y. H. Kwon, R. Kardon, and M. K. Garvin, “A combined machine-learning and graph-based framework for the segmentation of retinal surfaces in SD-OCT volumes,” Biomed. Opt. Express 4(12), 2712–2728 (2013).
[Crossref] [PubMed]

Q. Yang, C. A. Reisman, K. Chan, R. Ramachandran, A. Raza, and D. C. Hood, “Automated segmentation of outer retinal layers in macular OCT images of patients with retinitis pigmentosa,” Biomed. Opt. Express 2(9), 2493–2503 (2011).
[Crossref] [PubMed]

K. A. Vermeer, J. van der Schoot, H. G. Lemij, and J. F. de Boer, “Automated segmentation by pixel classification of retinal layers in ophthalmic OCT images,” Biomed. Opt. Express 2(6), 1743–1756 (2011).
[Crossref] [PubMed]

A. Lang, A. Carass, M. Hauser, E. S. Sotirchos, P. A. Calabresi, H. S. Ying, and J. L. Prince, “Retinal layer segmentation of macular OCT images using boundary classification,” Biomed. Opt. Express 4(7), 1133–1152 (2013).
[Crossref] [PubMed]

M. A. Mayer, J. Hornegger, C. Y. Mardin, and R. P. Tornow, “Retinal Nerve Fiber Layer Segmentation on FD-OCT Scans of Normal Subjects and Glaucoma Patients,” Biomed. Opt. Express 1(5), 1358–1383 (2010).
[Crossref] [PubMed]

A. Carass, A. Lang, M. Hauser, P. A. Calabresi, H. S. Ying, and J. L. Prince, “Multiple-object geometric deformable model for segmentation of macular OCT,” Biomed. Opt. Express 5(4), 1062–1074 (2014).
[Crossref] [PubMed]

BMC Bioinformatics (1)

G. M. Somfai, E. Tátrai, L. Laurik, B. Varga, V. Ölvedy, H. Jiang, J. Wang, W. E. Smiddy, A. Somogyi, and D. C. DeBuc, “Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes,” BMC Bioinformatics 15(1), 106 (2014).
[Crossref] [PubMed]

EURASIP J. Adv. Signal Process. (1)

Y. Zhang, B. Zhang, F. Coenen, J. Xiao, and W. Lu, “One-class kernel subspace ensemble for medical image classification,” EURASIP J. Adv. Signal Process. 2014, 1–13 (2014).

IEEE Trans. Commun. (1)

P. J. Burt and E. H. Adelson, “The Laplacian Pyramid as a Compact Image Code,” IEEE Trans. Commun. 31(4), 532–540 (1983).
[Crossref]

IEEE Trans. Image Process. (1)

K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering,” IEEE Trans. Image Process. 16(8), 2080–2095 (2007).
[Crossref] [PubMed]

IEEE Trans. Med. Imaging (1)

D. C. Fernández, “Delineating Fluid-Filled Region Boundaries in Optical Coherence Tomography Images of the Retina,” IEEE Trans. Med. Imaging 24(8), 929–945 (2005).
[Crossref] [PubMed]

Invest. Ophthalmol. Vis. Sci. (6)

L. A. Paunescu, J. S. Schuman, L. L. Price, P. C. Stark, S. Beaton, H. Ishikawa, G. Wollstein, and J. G. Fujimoto, “Reproducibility of Nerve Fiber Thickness, Macular Thickness, and Optic Nerve Head Measurements Using StratusOCT,” Invest. Ophthalmol. Vis. Sci. 45(6), 1716–1724 (2004).
[Crossref] [PubMed]

Y.-Y. Liu, H. Ishikawa, M. Chen, G. Wollstein, J. S. Duker, J. G. Fujimoto, J. S. Schuman, and J. M. Rehg, “Computerized macular pathology diagnosis in spectral domain optical coherence tomography scans based on multiscale texture and shape features,” Invest. Ophthalmol. Vis. Sci. 52(11), 8316–8322 (2011).
[Crossref] [PubMed]

J. Y. Lee, S. J. Chiu, P. Srinivasan, J. A. Izatt, C. A. Toth, S. Farsiu, and G. J. Jaffe, “Fully Automatic Software for Quantification of Retinal Thickness and Volume in Eyes with Diabetic Macular Edema from Images Acquired by Cirrus and Spectralis Spectral Domain Optical Coherence Tomography Machines,” Invest. Ophthalmol. Vis. Sci. 54, 7595–7602 (2013).
[Crossref] [PubMed]

S. J. Chiu, J. A. Izatt, R. V. O’Connell, K. P. Winter, C. A. Toth, and S. Farsiu, “Validated Automatic Segmentation of AMD Pathology Including Drusen and Geographic Atrophy in SD-OCT Images,” Invest. Ophthalmol. Vis. Sci. 53(1), 53–61 (2012).
[Crossref] [PubMed]

H. Ishikawa, D. M. Stein, G. Wollstein, S. Beaton, J. G. Fujimoto, and J. S. Schuman, “Macular Segmentation with Optical Coherence Tomography,” Invest. Ophthalmol. Vis. Sci. 46(6), 2012–2017 (2005).
[Crossref] [PubMed]

C. Bowes Rickman, S. Farsiu, C. A. Toth, and M. Klingeborn, “Dry Age-Related Macular Degeneration: Mechanisms, Therapeutic Targets, and Imaging,” Invest. Ophthalmol. Vis. Sci. 54(14), ORSF68 (2013).
[Crossref] [PubMed]

J. Biomed. Opt. (1)

D. C. DeBuc, G. M. Somfai, S. Ranganathan, E. Tátrai, M. Ferencz, and C. A. Puliafito, “Reliability and reproducibility of macular segmentation using a custom-built optical coherence tomography retinal image analysis software,” J. Biomed. Opt. 14(6), 064023 (2009).
[Crossref] [PubMed]

Mach. Learn. (1)

C. Cortes and V. Vapnik, “Support-vector networks,” Mach. Learn. 20(3), 273–297 (1995).
[Crossref]

Ophthalmology (3)

O. Tan, G. Li, A. T.-H. Lu, R. Varma, and D. Huang, “Mapping of Macular Substructures with Optical Coherence Tomography for Glaucoma Diagnosis,” Ophthalmology 115(6), 949–956 (2008).

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, and C. A. Toth, “Quantitative Classification of Eyes with and without Intermediate Age-related Macular Degeneration Using Optical Coherence Tomography,” Ophthalmology 121(1), 162–172 (2014).

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[Crossref]

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Figures (4)

Fig. 1
Fig. 1 Overview of the algorithm for classifying SD-OCT volumes.
Fig. 2
Fig. 2 Retinal curvature flattening. (a) SD-OCT image. (b) Image with retinal curvature flattened.
Fig. 3
Fig. 3 HOG descriptor visualization. (a) Original SD-OCT image. (b) Denoised, flattened, and cropped image. (c) HOG descriptor visualization for each block.
Fig. 4
Fig. 4 Example SD-OCT images from normal (column 1), AMD (column 2), and DME (column 3) data sets. Note that the third and fourth rows are from the same subjects. The first three rows show the hallmark B-scans from each disease group. The B-scans in the fourth row of the diseased eyes show that classification based on a single B-scan may not be reliable (e.g. the DME B-scan in the fourth row maybe mistaken for a case of dry-AMD).

Tables (2)

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Table 1 SD-OCT scanning protocol for the study subjects.

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Table 2 Fraction of volumes correctly classified during cross-validation.

Metrics