Abstract

This work introduces and evaluates an automated intra-retinal segmentation method for spectral-domain optical coherence (SD-OCT) retinal images. While quantitative assessment of retinal features in SD-OCT data is important, manual segmentation is extremely time-consuming and subjective. We address challenges that have hindered prior automated methods, including poor performance with diseased retinas relative to healthy retinas, and data smoothing that obscures image features such as small retinal drusen. Our novel segmentation approach is based on the iterative adaptation of a weighted median process, wherein a three-dimensional weighting function is defined according to image intensity and gradient properties, and a set of smoothness constraints and pre-defined rules are considered. We compared the segmentation results for 9 segmented outlines associated with intra-retinal boundaries to those drawn by hand by two retinal specialists and to those produced by an independent state-of-the-art automated software tool in a set of 42 clinical images (from 14 patients). These images were obtained with a Zeiss Cirrus SD-OCT system, including healthy, early or intermediate AMD, and advanced AMD eyes. As a qualitative evaluation of accuracy, a highly experienced third independent reader blindly rated the quality of the outlines produced by each method. The accuracy and image detail of our method was superior in healthy and early or intermediate AMD eyes (98.15% and 97.78% of results not needing substantial editing) to the automated method we compared against. While the performance was not as good in advanced AMD (68.89%), it was still better than the manual outlines or the comparison method (which failed in such cases). We also tested our method’s performance on images acquired with a different SD-OCT manufacturer, collected from a large publicly available data set (114 healthy and 255 AMD eyes), and compared the data quantitatively to reference standard markings of the internal limiting membrane and inner boundary of retinal pigment epithelium, producing a mean unsigned positioning error of 6.04 ± 7.83µm (mean under 2 pixels). Our automated method should be applicable to data from different OCT manufacturers and offers detailed layer segmentations in healthy and AMD eyes.

© 2017 Optical Society of America

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  1. D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
    [Crossref] [PubMed]
  2. J. R. Lee, J. W. Jeoung, J. Choi, J. Y. Choi, K. H. Park, and Y. D. Kim, “Structure-function relationships in normal and glaucomatous eyes determined by time- and spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6424–6430 (2010).
    [Crossref] [PubMed]
  3. L. de Sisternes, N. Simon, R. Tibshirani, T. Leng, and D. L. Rubin, “Quantitative SD-OCT imaging biomarkers as indicators of age-related macular degeneration progression,” Invest. Ophthalmol. Vis. Sci. 55(11), 7093–7103 (2014).
    [Crossref] [PubMed]
  4. K. Yi, M. Mujat, B. H. Park, W. Sun, J. W. Miller, J. M. Seddon, L. H. Young, J. F. de Boer, and T. C. Chen, “Spectral domain optical coherence tomography for quantitative evaluation of drusen and associated structural changes in non-neovascular age-related macular degeneration,” Br. J. Ophthalmol. 93(2), 176–181 (2009).
    [Crossref] [PubMed]
  5. G. Quellec, K. Lee, M. Dolejsi, M. K. Garvin, M. D. Abràmoff, and M. Sonka, “Three-dimensional analysis of retinal layer texture: identification of fluid-filled regions in SD-OCT of the macula,” IEEE Trans. Med. Imaging 29(6), 1321–1330 (2010).
    [Crossref] [PubMed]
  6. L. de Sisternes, J. Hu, D. L. Rubin, and T. Leng, “Visual prognosis of eyes recovering from macular hole surgery through automated quantitative analysis of spectral-domain optical coherence tomography (SD-OCT) scans,” Invest. Ophthalmol. Vis. Sci. 56(8), 4631–4643 (2015).
    [Crossref] [PubMed]
  7. J. H. Acton, R. T. Smith, D. C. Hood, and V. C. Greenstein, “Relationship between retinal layer thickness and the visual field in early age-related macular degeneration,” Invest. Ophthalmol. Vis. Sci. 53(12), 7618–7624 (2012).
    [Crossref] [PubMed]
  8. F. L. Ferris, M. D. Davis, T. E. Clemons, L. Y. Lee, E. Y. Chew, A. S. Lindblad, R. C. Milton, S. B. Bressler, R. Klein, and Age-Related Eye Disease Study (AREDS) Research Group, “A simplified severity scale for age-related macular degeneration: AREDS Report No. 18,” Arch. Ophthalmol. 123(11), 1570–1574 (2005).
    [Crossref] [PubMed]
  9. Q. Chen, T. Leng, L. Zheng, L. Kutzscher, J. Ma, L. de Sisternes, and D. L. Rubin, “Automated drusen segmentation and quantification in SD-OCT images,” Med. Image Anal. 17(8), 1058–1072 (2013).
    [Crossref] [PubMed]
  10. S. Y. Lee, P. F. Stetson, H. Ruiz-Garcia, F. M. Heussen, and S. R. Sadda, “Automated characterization of pigment epithelial detachment by optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53(1), 164–170 (2012).
    [Crossref] [PubMed]
  11. P. A. Keane, P. S. Mand, S. Liakopoulos, A. C. Walsh, and S. R. Sadda, “Accuracy of retinal thickness measurements obtained with Cirrus optical coherence tomography,” Br. J. Ophthalmol. 93(11), 1461–1467 (2009).
    [Crossref] [PubMed]
  12. G. Matt, S. Sacu, W. Buehl, C. Ahlers, R. Dunavoelgyi, C. Pruente, and U. Schmidt-Erfurth, “Comparison of retinal thickness values and segmentation performance of different OCT devices in acute branch retinal vein occlusion,” Eye (Lond.) 25(4), 511–518 (2011).
    [Crossref] [PubMed]
  13. F. G. Schlanitz, C. Ahlers, S. Sacu, C. Schütze, M. Rodriguez, S. Schriefl, I. Golbaz, T. Spalek, G. Stock, and U. Schmidt-Erfurth, “Performance of drusen detection by spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6715–6721 (2010).
    [Crossref] [PubMed]
  14. C. Ahlers, C. Simader, W. Geitzenauer, G. Stock, P. Stetson, S. Dastmalchi, and U. Schmidt-Erfurth, “Automatic segmentation in three-dimensional analysis of fibrovascular pigmentepithelial detachment using high-definition optical coherence tomography,” Br. J. Ophthalmol. 92(2), 197–203 (2008).
    [Crossref] [PubMed]
  15. L. de Sisternes, J. Hu, D. L. Rubin, and M. F. Marmor, “Localization of damage in progressive hydroxychloroquine retinopathy on and off the drug: inner versus outer retina, parafovea versus peripheral fovea,” Invest. Ophthalmol. Vis. Sci. 56(5), 3415–3426 (2015).
    [Crossref] [PubMed]
  16. H. J. Lee, M. S. Kim, Y. J. Jo, and J. Y. Kim, “Thickness of the macula, retinal nerve fiber layer, and ganglion cell layer in the epiretinal membrane: The repeatability study of optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 56(8), 4554–4559 (2015).
    [Crossref] [PubMed]
  17. H. J. Lee, M. S. Kim, Y. J. Jo, and J. Y. Kim, “Ganglion cell–inner plexiform layer thickness in retinal diseases: Repeatability study of spectral-domain optical coherence tomography,” Am. J. Ophthalmol. 160(2), 283–289 (2015).
    [Crossref] [PubMed]
  18. 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]
  19. 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]
  20. K. Li, X. Wu, D. Z. Chen, and M. Sonka, “Optimal surface segmentation in volumetric images--a graph-theoretic approach,” IEEE Trans. Pattern Anal. Mach. Intell. 28(1), 119–134 (2006).
    [Crossref] [PubMed]
  21. M. K. Garvin, M. D. Abramoff, R. Kardon, S. R. Russell, X. Wu, and M. Sonka, “Intraretinal layer segmentation of macular optical coherence tomography images using optimal 3-D graph search,” IEEE Trans. Med. Imaging 27(10), 1495–1505 (2008).
    [Crossref] [PubMed]
  22. M. K. Garvin, M. D. Abràmoff, X. Wu, S. R. Russell, T. L. Burns, and M. Sonka, “Automated 3-D intraretinal layer segmentation of macular spectral-domain optical coherence tomography images,” IEEE Trans. Med. Imaging 28(9), 1436–1447 (2009).
    [Crossref] [PubMed]
  23. P. A. Dufour, L. Ceklic, H. Abdillahi, S. Schröder, S. De Dzanet, U. Wolf-Schnurrbusch, and J. Kowal, “Graph-based multi-surface segmentation of OCT data using trained hard and soft constraints,” IEEE Trans. Med. Imaging 32(3), 531–543 (2013).
    [Crossref] [PubMed]
  24. S. J. Chiu, M. J. Allingham, P. S. Mettu, S. W. Cousins, J. A. Izatt, and S. Farsiu, “Kernel regression based segmentation of optical coherence tomography images with diabetic macular edema,” Biomed. Opt. Express 6(4), 1172–1194 (2015).
    [Crossref] [PubMed]
  25. K. Lee, M. D. Abramoff, M. Garvin, and M. Sonka, “The Iowa Reference Algorithms. (Retinal Image Analysis Lab, Iowa Institute for Biomedical Imaging),” (accessed 12 Jan 2015, Updated 29 Sep 2014). https://www.iibi.uiowa.edu/content/iowa-reference-algorithms-human-and-murine-oct-retinal-layer-analysis-and-display
  26. 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]
  27. 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]
  28. A. Ehnes, Y. Wenner, C. Friedburg, M. N. Preising, W. Bowl, W. Sekundo, E. M. Zu Bexten, K. Stieger, and B. Lorenz, “Optical coherence tomography (OCT) device independent intraretinal layer segmentation,” Transl. Vis. Sci. Technol. 3(1), 1–16 (2014).
    [Crossref] [PubMed]
  29. H. Ishikawa, S. Piette, J. M. Liebmann, and R. Ritch, “Detecting the inner and outer borders of the retinal nerve fiber layer using optical coherence tomography,” Graefes Arch. Clin. Exp. Ophthalmol. 240(5), 362–371 (2002).
    [Crossref] [PubMed]
  30. 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]
  31. H. Ishikawa, J. Kim, T. R. Friberg, G. Wollstein, L. Kagemann, M. L. Gabriele, K. A. Townsend, K. R. Sung, J. S. Duker, J. G. Fujimoto, and J. S. Schuman, “Three-dimensional optical coherence tomography (3D-OCT) image enhancement with segmentation-free contour modeling C-mode,” Invest. Ophthalmol. Vis. Sci. 50(3), 1344–1349 (2009).
    [Crossref] [PubMed]
  32. N. Jain, S. Farsiu, A. A. Khanifar, S. Bearelly, R. T. Smith, J. A. Izatt, and C. A. Toth, “Quantitative comparison of drusen segmented on SD-OCT versus drusen delineated on color fundus photographs,” Invest. Ophthalmol. Vis. Sci. 51(10), 4875–4883 (2010).
    [Crossref] [PubMed]
  33. R. Kafieh, H. Rabbani, M. D. Abramoff, and M. Sonka, “Intra-retinal layer segmentation of 3D optical coherence tomography using coarse grained diffusion map,” Med. Image Anal. 17(8), 907–928 (2013).
    [Crossref] [PubMed]
  34. 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]
  35. 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]
  36. 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]
  37. S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, and C. A. Toth, “World’s largest annotated SD-OCT dataset for intermediate AMD and control subjects used in our recent paper” (accessed July 2013). http://people.duke.edu/~sf59/RPEDC_Ophth_2013_dataset.htm .
  38. S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, C. A. Toth, and Age-Related Eye Disease Study 2 Ancillary Spectral Domain Optical Coherence Tomography Study Group, “Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography,” Ophthalmology 121(1), 162–172 (2014).
    [Crossref] [PubMed]
  39. G. Staurenghi, S. Sadda, U. Chakravarthy, R. F. Spaide, and International Nomenclature for Optical Coherence Tomography (IN•OCT) Panel, “Proposed lexicon for anatomic landmarks in normal posterior segment spectral-domain optical coherence tomography: the IN•OCT consensus,” Ophthalmology 121(8), 1572–1578 (2014).
    [Crossref] [PubMed]
  40. A. Buades, B. Coll, and J. M. Morel, “A non-local algorithm for image denoising,” Comput. Vis. Patt. Recog. 2(7), 60–65 (2005).
  41. S. Parrilli, M. Poderico, C. V. Angelino, G. Scarpa, and L. Verdoliva, “A non local approach for SAR image denoising,” IEEE Geoscience and Remote Sensing Symposium (IGARSS) (2010).
  42. L. Fang, S. Li, R. P. McNabb, Q. Nie, A. N. Kuo, C. A. Toth, J. A. Izatt, and S. Farsiu, “Fast acquisition and reconstruction of optical coherence tomography images via sparse representation,” IEEE Trans. Med. Imaging 32(11), 2034–2049 (2013).
    [Crossref] [PubMed]
  43. D. R. K. Brownrigg, “The weighted median filter,” Commun. Assoc. Comput. Machinery 27(8), 807–818 (1984).
  44. L. Yin, R. K. Yang, M. Gabbouj, and Y. Neuvo, “Weighted median filters: A tutorial,” IEEE Trans. Circuits Syst. II Analog Digit. Siganl Process. 43(3), 157–192 (1996).
    [Crossref]
  45. A. Buades, B. Coll, and J. M. Morel, “The staircasing effect in neighborhood filters and its solution,” IEEE Trans. Image Process. 15(6), 1499–1505 (2006).
    [Crossref] [PubMed]
  46. 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]
  47. J. D’Errico, “Surface Fitting using gridfit” (MATLAB CENTRAL File Exchange, 12 Jul 2013, Updated 29 Jul 2010). http://www.mathworks.com/matlabcentral/fileexchange/8998-surface-fitting-using-gridfit .
  48. S. J. Chiu, J. A. Izatt, R. V. O’Connell, K. P. Winter, C. A. Toth, and S. Farsiu, “Dataset for SD-OCT Retinal Image Analysis” (2012). http://people.duke.edu/~sf59/Chiu_IOVS_2011_dataset.htm .
  49. Teng, and Pang-yu. “Caserel - An Open Source Software for Computer-aided Segmentation of Retinal Layers in Optical Coherence Tomography Images” (2013). http://pangyuteng.github.io/caserel/
  50. M. Mayer, “Optical coherence tomography segmentation and evaluation GUI” (2016). https://www5.cs.fau.de/research/software/octseg/
  51. P. A. Dufour, “OCT segmentation application” (2012). http://pascaldufour.net/Research/software_data.html
  52. J. A. Hartigan and M. A. Wong, “Algorithm AS 136: A K-means clustering algorithm,” J. R. Stat. Soc. Series C 28(1), 100–108 (1979).

2015 (5)

L. de Sisternes, J. Hu, D. L. Rubin, and T. Leng, “Visual prognosis of eyes recovering from macular hole surgery through automated quantitative analysis of spectral-domain optical coherence tomography (SD-OCT) scans,” Invest. Ophthalmol. Vis. Sci. 56(8), 4631–4643 (2015).
[Crossref] [PubMed]

L. de Sisternes, J. Hu, D. L. Rubin, and M. F. Marmor, “Localization of damage in progressive hydroxychloroquine retinopathy on and off the drug: inner versus outer retina, parafovea versus peripheral fovea,” Invest. Ophthalmol. Vis. Sci. 56(5), 3415–3426 (2015).
[Crossref] [PubMed]

H. J. Lee, M. S. Kim, Y. J. Jo, and J. Y. Kim, “Thickness of the macula, retinal nerve fiber layer, and ganglion cell layer in the epiretinal membrane: The repeatability study of optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 56(8), 4554–4559 (2015).
[Crossref] [PubMed]

H. J. Lee, M. S. Kim, Y. J. Jo, and J. Y. Kim, “Ganglion cell–inner plexiform layer thickness in retinal diseases: Repeatability study of spectral-domain optical coherence tomography,” Am. J. Ophthalmol. 160(2), 283–289 (2015).
[Crossref] [PubMed]

S. J. Chiu, M. J. Allingham, P. S. Mettu, S. W. Cousins, J. A. Izatt, and S. Farsiu, “Kernel regression based segmentation of optical coherence tomography images with diabetic macular edema,” Biomed. Opt. Express 6(4), 1172–1194 (2015).
[Crossref] [PubMed]

2014 (4)

A. Ehnes, Y. Wenner, C. Friedburg, M. N. Preising, W. Bowl, W. Sekundo, E. M. Zu Bexten, K. Stieger, and B. Lorenz, “Optical coherence tomography (OCT) device independent intraretinal layer segmentation,” Transl. Vis. Sci. Technol. 3(1), 1–16 (2014).
[Crossref] [PubMed]

L. de Sisternes, N. Simon, R. Tibshirani, T. Leng, and D. L. Rubin, “Quantitative SD-OCT imaging biomarkers as indicators of age-related macular degeneration progression,” Invest. Ophthalmol. Vis. Sci. 55(11), 7093–7103 (2014).
[Crossref] [PubMed]

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, C. A. Toth, and Age-Related Eye Disease Study 2 Ancillary Spectral Domain Optical Coherence Tomography Study Group, “Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography,” Ophthalmology 121(1), 162–172 (2014).
[Crossref] [PubMed]

G. Staurenghi, S. Sadda, U. Chakravarthy, R. F. Spaide, and International Nomenclature for Optical Coherence Tomography (IN•OCT) Panel, “Proposed lexicon for anatomic landmarks in normal posterior segment spectral-domain optical coherence tomography: the IN•OCT consensus,” Ophthalmology 121(8), 1572–1578 (2014).
[Crossref] [PubMed]

2013 (5)

L. Fang, S. Li, R. P. McNabb, Q. Nie, A. N. Kuo, C. A. Toth, J. A. Izatt, and S. Farsiu, “Fast acquisition and reconstruction of optical coherence tomography images via sparse representation,” IEEE Trans. Med. Imaging 32(11), 2034–2049 (2013).
[Crossref] [PubMed]

Q. Chen, T. Leng, L. Zheng, L. Kutzscher, J. Ma, L. de Sisternes, and D. L. Rubin, “Automated drusen segmentation and quantification in SD-OCT images,” Med. Image Anal. 17(8), 1058–1072 (2013).
[Crossref] [PubMed]

P. A. Dufour, L. Ceklic, H. Abdillahi, S. Schröder, S. De Dzanet, U. Wolf-Schnurrbusch, and J. Kowal, “Graph-based multi-surface segmentation of OCT data using trained hard and soft constraints,” IEEE Trans. Med. Imaging 32(3), 531–543 (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]

R. Kafieh, H. Rabbani, M. D. Abramoff, and M. Sonka, “Intra-retinal layer segmentation of 3D optical coherence tomography using coarse grained diffusion map,” Med. Image Anal. 17(8), 907–928 (2013).
[Crossref] [PubMed]

2012 (3)

S. Y. Lee, P. F. Stetson, H. Ruiz-Garcia, F. M. Heussen, and S. R. Sadda, “Automated characterization of pigment epithelial detachment by optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53(1), 164–170 (2012).
[Crossref] [PubMed]

J. H. Acton, R. T. Smith, D. C. Hood, and V. C. Greenstein, “Relationship between retinal layer thickness and the visual field in early age-related macular degeneration,” Invest. Ophthalmol. Vis. Sci. 53(12), 7618–7624 (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]

2011 (2)

G. Matt, S. Sacu, W. Buehl, C. Ahlers, R. Dunavoelgyi, C. Pruente, and U. Schmidt-Erfurth, “Comparison of retinal thickness values and segmentation performance of different OCT devices in acute branch retinal vein occlusion,” Eye (Lond.) 25(4), 511–518 (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]

2010 (6)

G. Quellec, K. Lee, M. Dolejsi, M. K. Garvin, M. D. Abràmoff, and M. Sonka, “Three-dimensional analysis of retinal layer texture: identification of fluid-filled regions in SD-OCT of the macula,” IEEE Trans. Med. Imaging 29(6), 1321–1330 (2010).
[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]

N. Jain, S. Farsiu, A. A. Khanifar, S. Bearelly, R. T. Smith, J. A. Izatt, and C. A. Toth, “Quantitative comparison of drusen segmented on SD-OCT versus drusen delineated on color fundus photographs,” Invest. Ophthalmol. Vis. Sci. 51(10), 4875–4883 (2010).
[Crossref] [PubMed]

F. G. Schlanitz, C. Ahlers, S. Sacu, C. Schütze, M. Rodriguez, S. Schriefl, I. Golbaz, T. Spalek, G. Stock, and U. Schmidt-Erfurth, “Performance of drusen detection by spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6715–6721 (2010).
[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]

J. R. Lee, J. W. Jeoung, J. Choi, J. Y. Choi, K. H. Park, and Y. D. Kim, “Structure-function relationships in normal and glaucomatous eyes determined by time- and spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6424–6430 (2010).
[Crossref] [PubMed]

2009 (5)

K. Yi, M. Mujat, B. H. Park, W. Sun, J. W. Miller, J. M. Seddon, L. H. Young, J. F. de Boer, and T. C. Chen, “Spectral domain optical coherence tomography for quantitative evaluation of drusen and associated structural changes in non-neovascular age-related macular degeneration,” Br. J. Ophthalmol. 93(2), 176–181 (2009).
[Crossref] [PubMed]

P. A. Keane, P. S. Mand, S. Liakopoulos, A. C. Walsh, and S. R. Sadda, “Accuracy of retinal thickness measurements obtained with Cirrus optical coherence tomography,” Br. J. Ophthalmol. 93(11), 1461–1467 (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]

H. Ishikawa, J. Kim, T. R. Friberg, G. Wollstein, L. Kagemann, M. L. Gabriele, K. A. Townsend, K. R. Sung, J. S. Duker, J. G. Fujimoto, and J. S. Schuman, “Three-dimensional optical coherence tomography (3D-OCT) image enhancement with segmentation-free contour modeling C-mode,” Invest. Ophthalmol. Vis. Sci. 50(3), 1344–1349 (2009).
[Crossref] [PubMed]

M. K. Garvin, M. D. Abràmoff, X. Wu, S. R. Russell, T. L. Burns, and M. Sonka, “Automated 3-D intraretinal layer segmentation of macular spectral-domain optical coherence tomography images,” IEEE Trans. Med. Imaging 28(9), 1436–1447 (2009).
[Crossref] [PubMed]

2008 (2)

M. K. Garvin, M. D. Abramoff, R. Kardon, S. R. Russell, X. Wu, and M. Sonka, “Intraretinal layer segmentation of macular optical coherence tomography images using optimal 3-D graph search,” IEEE Trans. Med. Imaging 27(10), 1495–1505 (2008).
[Crossref] [PubMed]

C. Ahlers, C. Simader, W. Geitzenauer, G. Stock, P. Stetson, S. Dastmalchi, and U. Schmidt-Erfurth, “Automatic segmentation in three-dimensional analysis of fibrovascular pigmentepithelial detachment using high-definition optical coherence tomography,” Br. J. Ophthalmol. 92(2), 197–203 (2008).
[Crossref] [PubMed]

2006 (2)

K. Li, X. Wu, D. Z. Chen, and M. Sonka, “Optimal surface segmentation in volumetric images--a graph-theoretic approach,” IEEE Trans. Pattern Anal. Mach. Intell. 28(1), 119–134 (2006).
[Crossref] [PubMed]

A. Buades, B. Coll, and J. M. Morel, “The staircasing effect in neighborhood filters and its solution,” IEEE Trans. Image Process. 15(6), 1499–1505 (2006).
[Crossref] [PubMed]

2005 (5)

A. Buades, B. Coll, and J. M. Morel, “A non-local algorithm for image denoising,” Comput. Vis. Patt. Recog. 2(7), 60–65 (2005).

F. L. Ferris, M. D. Davis, T. E. Clemons, L. Y. Lee, E. Y. Chew, A. S. Lindblad, R. C. Milton, S. B. Bressler, R. Klein, and Age-Related Eye Disease Study (AREDS) Research Group, “A simplified severity scale for age-related macular degeneration: AREDS Report No. 18,” Arch. Ophthalmol. 123(11), 1570–1574 (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. 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]

2002 (1)

H. Ishikawa, S. Piette, J. M. Liebmann, and R. Ritch, “Detecting the inner and outer borders of the retinal nerve fiber layer using optical coherence tomography,” Graefes Arch. Clin. Exp. Ophthalmol. 240(5), 362–371 (2002).
[Crossref] [PubMed]

1996 (1)

L. Yin, R. K. Yang, M. Gabbouj, and Y. Neuvo, “Weighted median filters: A tutorial,” IEEE Trans. Circuits Syst. II Analog Digit. Siganl Process. 43(3), 157–192 (1996).
[Crossref]

1991 (1)

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

1984 (1)

D. R. K. Brownrigg, “The weighted median filter,” Commun. Assoc. Comput. Machinery 27(8), 807–818 (1984).

1979 (1)

J. A. Hartigan and M. A. Wong, “Algorithm AS 136: A K-means clustering algorithm,” J. R. Stat. Soc. Series C 28(1), 100–108 (1979).

Abdillahi, H.

P. A. Dufour, L. Ceklic, H. Abdillahi, S. Schröder, S. De Dzanet, U. Wolf-Schnurrbusch, and J. Kowal, “Graph-based multi-surface segmentation of OCT data using trained hard and soft constraints,” IEEE Trans. Med. Imaging 32(3), 531–543 (2013).
[Crossref] [PubMed]

Abramoff, M. D.

R. Kafieh, H. Rabbani, M. D. Abramoff, and M. Sonka, “Intra-retinal layer segmentation of 3D optical coherence tomography using coarse grained diffusion map,” Med. Image Anal. 17(8), 907–928 (2013).
[Crossref] [PubMed]

M. K. Garvin, M. D. Abramoff, R. Kardon, S. R. Russell, X. Wu, and M. Sonka, “Intraretinal layer segmentation of macular optical coherence tomography images using optimal 3-D graph search,” IEEE Trans. Med. Imaging 27(10), 1495–1505 (2008).
[Crossref] [PubMed]

Abràmoff, M. D.

G. Quellec, K. Lee, M. Dolejsi, M. K. Garvin, M. D. Abràmoff, and M. Sonka, “Three-dimensional analysis of retinal layer texture: identification of fluid-filled regions in SD-OCT of the macula,” IEEE Trans. Med. Imaging 29(6), 1321–1330 (2010).
[Crossref] [PubMed]

M. K. Garvin, M. D. Abràmoff, X. Wu, S. R. Russell, T. L. Burns, and M. Sonka, “Automated 3-D intraretinal layer segmentation of macular spectral-domain optical coherence tomography images,” IEEE Trans. Med. Imaging 28(9), 1436–1447 (2009).
[Crossref] [PubMed]

Acton, J. H.

J. H. Acton, R. T. Smith, D. C. Hood, and V. C. Greenstein, “Relationship between retinal layer thickness and the visual field in early age-related macular degeneration,” Invest. Ophthalmol. Vis. Sci. 53(12), 7618–7624 (2012).
[Crossref] [PubMed]

Ahlers, C.

G. Matt, S. Sacu, W. Buehl, C. Ahlers, R. Dunavoelgyi, C. Pruente, and U. Schmidt-Erfurth, “Comparison of retinal thickness values and segmentation performance of different OCT devices in acute branch retinal vein occlusion,” Eye (Lond.) 25(4), 511–518 (2011).
[Crossref] [PubMed]

F. G. Schlanitz, C. Ahlers, S. Sacu, C. Schütze, M. Rodriguez, S. Schriefl, I. Golbaz, T. Spalek, G. Stock, and U. Schmidt-Erfurth, “Performance of drusen detection by spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6715–6721 (2010).
[Crossref] [PubMed]

C. Ahlers, C. Simader, W. Geitzenauer, G. Stock, P. Stetson, S. Dastmalchi, and U. Schmidt-Erfurth, “Automatic segmentation in three-dimensional analysis of fibrovascular pigmentepithelial detachment using high-definition optical coherence tomography,” Br. J. Ophthalmol. 92(2), 197–203 (2008).
[Crossref] [PubMed]

Akkin, T.

Allingham, M. J.

Angelino, C. V.

S. Parrilli, M. Poderico, C. V. Angelino, G. Scarpa, and L. Verdoliva, “A non local approach for SAR image denoising,” IEEE Geoscience and Remote Sensing Symposium (IGARSS) (2010).

Bearelly, S.

N. Jain, S. Farsiu, A. A. Khanifar, S. Bearelly, R. T. Smith, J. A. Izatt, and C. A. Toth, “Quantitative comparison of drusen segmented on SD-OCT versus drusen delineated on color fundus photographs,” Invest. Ophthalmol. Vis. Sci. 51(10), 4875–4883 (2010).
[Crossref] [PubMed]

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]

Bizheva, K.

Bowl, W.

A. Ehnes, Y. Wenner, C. Friedburg, M. N. Preising, W. Bowl, W. Sekundo, E. M. Zu Bexten, K. Stieger, and B. Lorenz, “Optical coherence tomography (OCT) device independent intraretinal layer segmentation,” Transl. Vis. Sci. Technol. 3(1), 1–16 (2014).
[Crossref] [PubMed]

Bressler, S. B.

F. L. Ferris, M. D. Davis, T. E. Clemons, L. Y. Lee, E. Y. Chew, A. S. Lindblad, R. C. Milton, S. B. Bressler, R. Klein, and Age-Related Eye Disease Study (AREDS) Research Group, “A simplified severity scale for age-related macular degeneration: AREDS Report No. 18,” Arch. Ophthalmol. 123(11), 1570–1574 (2005).
[Crossref] [PubMed]

Brownrigg, D. R. K.

D. R. K. Brownrigg, “The weighted median filter,” Commun. Assoc. Comput. Machinery 27(8), 807–818 (1984).

Buades, A.

A. Buades, B. Coll, and J. M. Morel, “The staircasing effect in neighborhood filters and its solution,” IEEE Trans. Image Process. 15(6), 1499–1505 (2006).
[Crossref] [PubMed]

A. Buades, B. Coll, and J. M. Morel, “A non-local algorithm for image denoising,” Comput. Vis. Patt. Recog. 2(7), 60–65 (2005).

Buehl, W.

G. Matt, S. Sacu, W. Buehl, C. Ahlers, R. Dunavoelgyi, C. Pruente, and U. Schmidt-Erfurth, “Comparison of retinal thickness values and segmentation performance of different OCT devices in acute branch retinal vein occlusion,” Eye (Lond.) 25(4), 511–518 (2011).
[Crossref] [PubMed]

Burns, T. L.

M. K. Garvin, M. D. Abràmoff, X. Wu, S. R. Russell, T. L. Burns, and M. Sonka, “Automated 3-D intraretinal layer segmentation of macular spectral-domain optical coherence tomography images,” IEEE Trans. Med. Imaging 28(9), 1436–1447 (2009).
[Crossref] [PubMed]

Cabrera Fernández, D.

Calabresi, P. A.

Carass, A.

Ceklic, L.

P. A. Dufour, L. Ceklic, H. Abdillahi, S. Schröder, S. De Dzanet, U. Wolf-Schnurrbusch, and J. Kowal, “Graph-based multi-surface segmentation of OCT data using trained hard and soft constraints,” IEEE Trans. Med. Imaging 32(3), 531–543 (2013).
[Crossref] [PubMed]

Cense, B.

Chakravarthy, U.

G. Staurenghi, S. Sadda, U. Chakravarthy, R. F. Spaide, and International Nomenclature for Optical Coherence Tomography (IN•OCT) Panel, “Proposed lexicon for anatomic landmarks in normal posterior segment spectral-domain optical coherence tomography: the IN•OCT consensus,” Ophthalmology 121(8), 1572–1578 (2014).
[Crossref] [PubMed]

Chan, R.

Chang, W.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Chen, D. Z.

K. Li, X. Wu, D. Z. Chen, and M. Sonka, “Optimal surface segmentation in volumetric images--a graph-theoretic approach,” IEEE Trans. Pattern Anal. Mach. Intell. 28(1), 119–134 (2006).
[Crossref] [PubMed]

Chen, Q.

Q. Chen, T. Leng, L. Zheng, L. Kutzscher, J. Ma, L. de Sisternes, and D. L. Rubin, “Automated drusen segmentation and quantification in SD-OCT images,” Med. Image Anal. 17(8), 1058–1072 (2013).
[Crossref] [PubMed]

Chen, T.

Chen, T. C.

K. Yi, M. Mujat, B. H. Park, W. Sun, J. W. Miller, J. M. Seddon, L. H. Young, J. F. de Boer, and T. C. Chen, “Spectral domain optical coherence tomography for quantitative evaluation of drusen and associated structural changes in non-neovascular age-related macular degeneration,” Br. J. Ophthalmol. 93(2), 176–181 (2009).
[Crossref] [PubMed]

Chew, E. Y.

F. L. Ferris, M. D. Davis, T. E. Clemons, L. Y. Lee, E. Y. Chew, A. S. Lindblad, R. C. Milton, S. B. Bressler, R. Klein, and Age-Related Eye Disease Study (AREDS) Research Group, “A simplified severity scale for age-related macular degeneration: AREDS Report No. 18,” Arch. Ophthalmol. 123(11), 1570–1574 (2005).
[Crossref] [PubMed]

Chiu, S. J.

S. J. Chiu, M. J. Allingham, P. S. Mettu, S. W. Cousins, J. A. Izatt, and S. Farsiu, “Kernel regression based segmentation of optical coherence tomography images with diabetic macular edema,” Biomed. Opt. Express 6(4), 1172–1194 (2015).
[Crossref] [PubMed]

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, C. A. Toth, and Age-Related Eye Disease Study 2 Ancillary Spectral Domain Optical Coherence Tomography Study Group, “Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography,” Ophthalmology 121(1), 162–172 (2014).
[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, 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]

Choi, J.

J. R. Lee, J. W. Jeoung, J. Choi, J. Y. Choi, K. H. Park, and Y. D. Kim, “Structure-function relationships in normal and glaucomatous eyes determined by time- and spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6424–6430 (2010).
[Crossref] [PubMed]

Choi, J. Y.

J. R. Lee, J. W. Jeoung, J. Choi, J. Y. Choi, K. H. Park, and Y. D. Kim, “Structure-function relationships in normal and glaucomatous eyes determined by time- and spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6424–6430 (2010).
[Crossref] [PubMed]

Clausi, D. A.

Clemons, T. E.

F. L. Ferris, M. D. Davis, T. E. Clemons, L. Y. Lee, E. Y. Chew, A. S. Lindblad, R. C. Milton, S. B. Bressler, R. Klein, and Age-Related Eye Disease Study (AREDS) Research Group, “A simplified severity scale for age-related macular degeneration: AREDS Report No. 18,” Arch. Ophthalmol. 123(11), 1570–1574 (2005).
[Crossref] [PubMed]

Coll, B.

A. Buades, B. Coll, and J. M. Morel, “The staircasing effect in neighborhood filters and its solution,” IEEE Trans. Image Process. 15(6), 1499–1505 (2006).
[Crossref] [PubMed]

A. Buades, B. Coll, and J. M. Morel, “A non-local algorithm for image denoising,” Comput. Vis. Patt. Recog. 2(7), 60–65 (2005).

Cousins, S. W.

Dastmalchi, S.

C. Ahlers, C. Simader, W. Geitzenauer, G. Stock, P. Stetson, S. Dastmalchi, and U. Schmidt-Erfurth, “Automatic segmentation in three-dimensional analysis of fibrovascular pigmentepithelial detachment using high-definition optical coherence tomography,” Br. J. Ophthalmol. 92(2), 197–203 (2008).
[Crossref] [PubMed]

Davis, M. D.

F. L. Ferris, M. D. Davis, T. E. Clemons, L. Y. Lee, E. Y. Chew, A. S. Lindblad, R. C. Milton, S. B. Bressler, R. Klein, and Age-Related Eye Disease Study (AREDS) Research Group, “A simplified severity scale for age-related macular degeneration: AREDS Report No. 18,” Arch. Ophthalmol. 123(11), 1570–1574 (2005).
[Crossref] [PubMed]

de Boer, J.

de Boer, J. F.

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]

K. Yi, M. Mujat, B. H. Park, W. Sun, J. W. Miller, J. M. Seddon, L. H. Young, J. F. de Boer, and T. C. Chen, “Spectral domain optical coherence tomography for quantitative evaluation of drusen and associated structural changes in non-neovascular age-related macular degeneration,” Br. J. Ophthalmol. 93(2), 176–181 (2009).
[Crossref] [PubMed]

De Dzanet, S.

P. A. Dufour, L. Ceklic, H. Abdillahi, S. Schröder, S. De Dzanet, U. Wolf-Schnurrbusch, and J. Kowal, “Graph-based multi-surface segmentation of OCT data using trained hard and soft constraints,” IEEE Trans. Med. Imaging 32(3), 531–543 (2013).
[Crossref] [PubMed]

de Sisternes, L.

L. de Sisternes, J. Hu, D. L. Rubin, and T. Leng, “Visual prognosis of eyes recovering from macular hole surgery through automated quantitative analysis of spectral-domain optical coherence tomography (SD-OCT) scans,” Invest. Ophthalmol. Vis. Sci. 56(8), 4631–4643 (2015).
[Crossref] [PubMed]

L. de Sisternes, J. Hu, D. L. Rubin, and M. F. Marmor, “Localization of damage in progressive hydroxychloroquine retinopathy on and off the drug: inner versus outer retina, parafovea versus peripheral fovea,” Invest. Ophthalmol. Vis. Sci. 56(5), 3415–3426 (2015).
[Crossref] [PubMed]

L. de Sisternes, N. Simon, R. Tibshirani, T. Leng, and D. L. Rubin, “Quantitative SD-OCT imaging biomarkers as indicators of age-related macular degeneration progression,” Invest. Ophthalmol. Vis. Sci. 55(11), 7093–7103 (2014).
[Crossref] [PubMed]

Q. Chen, T. Leng, L. Zheng, L. Kutzscher, J. Ma, L. de Sisternes, and D. L. Rubin, “Automated drusen segmentation and quantification in SD-OCT images,” Med. Image Anal. 17(8), 1058–1072 (2013).
[Crossref] [PubMed]

Dolejsi, M.

G. Quellec, K. Lee, M. Dolejsi, M. K. Garvin, M. D. Abràmoff, and M. Sonka, “Three-dimensional analysis of retinal layer texture: identification of fluid-filled regions in SD-OCT of the macula,” IEEE Trans. Med. Imaging 29(6), 1321–1330 (2010).
[Crossref] [PubMed]

Dufour, P. A.

P. A. Dufour, L. Ceklic, H. Abdillahi, S. Schröder, S. De Dzanet, U. Wolf-Schnurrbusch, and J. Kowal, “Graph-based multi-surface segmentation of OCT data using trained hard and soft constraints,” IEEE Trans. Med. Imaging 32(3), 531–543 (2013).
[Crossref] [PubMed]

Duker, J. S.

H. Ishikawa, J. Kim, T. R. Friberg, G. Wollstein, L. Kagemann, M. L. Gabriele, K. A. Townsend, K. R. Sung, J. S. Duker, J. G. Fujimoto, and J. S. Schuman, “Three-dimensional optical coherence tomography (3D-OCT) image enhancement with segmentation-free contour modeling C-mode,” Invest. Ophthalmol. Vis. Sci. 50(3), 1344–1349 (2009).
[Crossref] [PubMed]

Dunavoelgyi, R.

G. Matt, S. Sacu, W. Buehl, C. Ahlers, R. Dunavoelgyi, C. Pruente, and U. Schmidt-Erfurth, “Comparison of retinal thickness values and segmentation performance of different OCT devices in acute branch retinal vein occlusion,” Eye (Lond.) 25(4), 511–518 (2011).
[Crossref] [PubMed]

Ehnes, A.

A. Ehnes, Y. Wenner, C. Friedburg, M. N. Preising, W. Bowl, W. Sekundo, E. M. Zu Bexten, K. Stieger, and B. Lorenz, “Optical coherence tomography (OCT) device independent intraretinal layer segmentation,” Transl. Vis. Sci. Technol. 3(1), 1–16 (2014).
[Crossref] [PubMed]

Fang, L.

L. Fang, S. Li, R. P. McNabb, Q. Nie, A. N. Kuo, C. A. Toth, J. A. Izatt, and S. Farsiu, “Fast acquisition and reconstruction of optical coherence tomography images via sparse representation,” IEEE Trans. Med. Imaging 32(11), 2034–2049 (2013).
[Crossref] [PubMed]

Farsiu, S.

S. J. Chiu, M. J. Allingham, P. S. Mettu, S. W. Cousins, J. A. Izatt, and S. Farsiu, “Kernel regression based segmentation of optical coherence tomography images with diabetic macular edema,” Biomed. Opt. Express 6(4), 1172–1194 (2015).
[Crossref] [PubMed]

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, C. A. Toth, and Age-Related Eye Disease Study 2 Ancillary Spectral Domain Optical Coherence Tomography Study Group, “Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography,” Ophthalmology 121(1), 162–172 (2014).
[Crossref] [PubMed]

L. Fang, S. Li, R. P. McNabb, Q. Nie, A. N. Kuo, C. A. Toth, J. A. Izatt, and S. Farsiu, “Fast acquisition and reconstruction of optical coherence tomography images via sparse representation,” IEEE Trans. Med. Imaging 32(11), 2034–2049 (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, 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]

N. Jain, S. Farsiu, A. A. Khanifar, S. Bearelly, R. T. Smith, J. A. Izatt, and C. A. Toth, “Quantitative comparison of drusen segmented on SD-OCT versus drusen delineated on color fundus photographs,” Invest. Ophthalmol. Vis. Sci. 51(10), 4875–4883 (2010).
[Crossref] [PubMed]

Ferris, F. L.

F. L. Ferris, M. D. Davis, T. E. Clemons, L. Y. Lee, E. Y. Chew, A. S. Lindblad, R. C. Milton, S. B. Bressler, R. Klein, and Age-Related Eye Disease Study (AREDS) Research Group, “A simplified severity scale for age-related macular degeneration: AREDS Report No. 18,” Arch. Ophthalmol. 123(11), 1570–1574 (2005).
[Crossref] [PubMed]

Flotte, T.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Folgar, F. A.

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, C. A. Toth, and Age-Related Eye Disease Study 2 Ancillary Spectral Domain Optical Coherence Tomography Study Group, “Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography,” Ophthalmology 121(1), 162–172 (2014).
[Crossref] [PubMed]

Friberg, T. R.

H. Ishikawa, J. Kim, T. R. Friberg, G. Wollstein, L. Kagemann, M. L. Gabriele, K. A. Townsend, K. R. Sung, J. S. Duker, J. G. Fujimoto, and J. S. Schuman, “Three-dimensional optical coherence tomography (3D-OCT) image enhancement with segmentation-free contour modeling C-mode,” Invest. Ophthalmol. Vis. Sci. 50(3), 1344–1349 (2009).
[Crossref] [PubMed]

Friedburg, C.

A. Ehnes, Y. Wenner, C. Friedburg, M. N. Preising, W. Bowl, W. Sekundo, E. M. Zu Bexten, K. Stieger, and B. Lorenz, “Optical coherence tomography (OCT) device independent intraretinal layer segmentation,” Transl. Vis. Sci. Technol. 3(1), 1–16 (2014).
[Crossref] [PubMed]

Fujimoto, J.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Fujimoto, J. G.

H. Ishikawa, J. Kim, T. R. Friberg, G. Wollstein, L. Kagemann, M. L. Gabriele, K. A. Townsend, K. R. Sung, J. S. Duker, J. G. Fujimoto, and J. S. Schuman, “Three-dimensional optical coherence tomography (3D-OCT) image enhancement with segmentation-free contour modeling C-mode,” Invest. Ophthalmol. Vis. Sci. 50(3), 1344–1349 (2009).
[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]

Gabbouj, M.

L. Yin, R. K. Yang, M. Gabbouj, and Y. Neuvo, “Weighted median filters: A tutorial,” IEEE Trans. Circuits Syst. II Analog Digit. Siganl Process. 43(3), 157–192 (1996).
[Crossref]

Gabriele, M. L.

H. Ishikawa, J. Kim, T. R. Friberg, G. Wollstein, L. Kagemann, M. L. Gabriele, K. A. Townsend, K. R. Sung, J. S. Duker, J. G. Fujimoto, and J. S. Schuman, “Three-dimensional optical coherence tomography (3D-OCT) image enhancement with segmentation-free contour modeling C-mode,” Invest. Ophthalmol. Vis. Sci. 50(3), 1344–1349 (2009).
[Crossref] [PubMed]

Garvin, M. K.

G. Quellec, K. Lee, M. Dolejsi, M. K. Garvin, M. D. Abràmoff, and M. Sonka, “Three-dimensional analysis of retinal layer texture: identification of fluid-filled regions in SD-OCT of the macula,” IEEE Trans. Med. Imaging 29(6), 1321–1330 (2010).
[Crossref] [PubMed]

M. K. Garvin, M. D. Abràmoff, X. Wu, S. R. Russell, T. L. Burns, and M. Sonka, “Automated 3-D intraretinal layer segmentation of macular spectral-domain optical coherence tomography images,” IEEE Trans. Med. Imaging 28(9), 1436–1447 (2009).
[Crossref] [PubMed]

M. K. Garvin, M. D. Abramoff, R. Kardon, S. R. Russell, X. Wu, and M. Sonka, “Intraretinal layer segmentation of macular optical coherence tomography images using optimal 3-D graph search,” IEEE Trans. Med. Imaging 27(10), 1495–1505 (2008).
[Crossref] [PubMed]

Geitzenauer, W.

C. Ahlers, C. Simader, W. Geitzenauer, G. Stock, P. Stetson, S. Dastmalchi, and U. Schmidt-Erfurth, “Automatic segmentation in three-dimensional analysis of fibrovascular pigmentepithelial detachment using high-definition optical coherence tomography,” Br. J. Ophthalmol. 92(2), 197–203 (2008).
[Crossref] [PubMed]

Golbaz, I.

F. G. Schlanitz, C. Ahlers, S. Sacu, C. Schütze, M. Rodriguez, S. Schriefl, I. Golbaz, T. Spalek, G. Stock, and U. Schmidt-Erfurth, “Performance of drusen detection by spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6715–6721 (2010).
[Crossref] [PubMed]

Greenstein, V. C.

J. H. Acton, R. T. Smith, D. C. Hood, and V. C. Greenstein, “Relationship between retinal layer thickness and the visual field in early age-related macular degeneration,” Invest. Ophthalmol. Vis. Sci. 53(12), 7618–7624 (2012).
[Crossref] [PubMed]

Gregory, K.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Hartigan, J. A.

J. A. Hartigan and M. A. Wong, “Algorithm AS 136: A K-means clustering algorithm,” J. R. Stat. Soc. Series C 28(1), 100–108 (1979).

Hauser, M.

Hee, M. R.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Heussen, F. M.

S. Y. Lee, P. F. Stetson, H. Ruiz-Garcia, F. M. Heussen, and S. R. Sadda, “Automated characterization of pigment epithelial detachment by optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53(1), 164–170 (2012).
[Crossref] [PubMed]

Hood, D. C.

J. H. Acton, R. T. Smith, D. C. Hood, and V. C. Greenstein, “Relationship between retinal layer thickness and the visual field in early age-related macular degeneration,” Invest. Ophthalmol. Vis. Sci. 53(12), 7618–7624 (2012).
[Crossref] [PubMed]

Hornegger, J.

Hu, J.

L. de Sisternes, J. Hu, D. L. Rubin, and T. Leng, “Visual prognosis of eyes recovering from macular hole surgery through automated quantitative analysis of spectral-domain optical coherence tomography (SD-OCT) scans,” Invest. Ophthalmol. Vis. Sci. 56(8), 4631–4643 (2015).
[Crossref] [PubMed]

L. de Sisternes, J. Hu, D. L. Rubin, and M. F. Marmor, “Localization of damage in progressive hydroxychloroquine retinopathy on and off the drug: inner versus outer retina, parafovea versus peripheral fovea,” Invest. Ophthalmol. Vis. Sci. 56(5), 3415–3426 (2015).
[Crossref] [PubMed]

Huang, D.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Ishikawa, H.

H. Ishikawa, J. Kim, T. R. Friberg, G. Wollstein, L. Kagemann, M. L. Gabriele, K. A. Townsend, K. R. Sung, J. S. Duker, J. G. Fujimoto, and J. S. Schuman, “Three-dimensional optical coherence tomography (3D-OCT) image enhancement with segmentation-free contour modeling C-mode,” Invest. Ophthalmol. Vis. Sci. 50(3), 1344–1349 (2009).
[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]

H. Ishikawa, S. Piette, J. M. Liebmann, and R. Ritch, “Detecting the inner and outer borders of the retinal nerve fiber layer using optical coherence tomography,” Graefes Arch. Clin. Exp. Ophthalmol. 240(5), 362–371 (2002).
[Crossref] [PubMed]

Izatt, J. A.

S. J. Chiu, M. J. Allingham, P. S. Mettu, S. W. Cousins, J. A. Izatt, and S. Farsiu, “Kernel regression based segmentation of optical coherence tomography images with diabetic macular edema,” Biomed. Opt. Express 6(4), 1172–1194 (2015).
[Crossref] [PubMed]

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, C. A. Toth, and Age-Related Eye Disease Study 2 Ancillary Spectral Domain Optical Coherence Tomography Study Group, “Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography,” Ophthalmology 121(1), 162–172 (2014).
[Crossref] [PubMed]

L. Fang, S. Li, R. P. McNabb, Q. Nie, A. N. Kuo, C. A. Toth, J. A. Izatt, and S. Farsiu, “Fast acquisition and reconstruction of optical coherence tomography images via sparse representation,” IEEE Trans. Med. Imaging 32(11), 2034–2049 (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, 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]

N. Jain, S. Farsiu, A. A. Khanifar, S. Bearelly, R. T. Smith, J. A. Izatt, and C. A. Toth, “Quantitative comparison of drusen segmented on SD-OCT versus drusen delineated on color fundus photographs,” Invest. Ophthalmol. Vis. Sci. 51(10), 4875–4883 (2010).
[Crossref] [PubMed]

Jain, N.

N. Jain, S. Farsiu, A. A. Khanifar, S. Bearelly, R. T. Smith, J. A. Izatt, and C. A. Toth, “Quantitative comparison of drusen segmented on SD-OCT versus drusen delineated on color fundus photographs,” Invest. Ophthalmol. Vis. Sci. 51(10), 4875–4883 (2010).
[Crossref] [PubMed]

Jeoung, J. W.

J. R. Lee, J. W. Jeoung, J. Choi, J. Y. Choi, K. H. Park, and Y. D. Kim, “Structure-function relationships in normal and glaucomatous eyes determined by time- and spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6424–6430 (2010).
[Crossref] [PubMed]

Jo, Y. J.

H. J. Lee, M. S. Kim, Y. J. Jo, and J. Y. Kim, “Thickness of the macula, retinal nerve fiber layer, and ganglion cell layer in the epiretinal membrane: The repeatability study of optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 56(8), 4554–4559 (2015).
[Crossref] [PubMed]

H. J. Lee, M. S. Kim, Y. J. Jo, and J. Y. Kim, “Ganglion cell–inner plexiform layer thickness in retinal diseases: Repeatability study of spectral-domain optical coherence tomography,” Am. J. Ophthalmol. 160(2), 283–289 (2015).
[Crossref] [PubMed]

Joo, C.

Kafieh, R.

R. Kafieh, H. Rabbani, M. D. Abramoff, and M. Sonka, “Intra-retinal layer segmentation of 3D optical coherence tomography using coarse grained diffusion map,” Med. Image Anal. 17(8), 907–928 (2013).
[Crossref] [PubMed]

Kagemann, L.

H. Ishikawa, J. Kim, T. R. Friberg, G. Wollstein, L. Kagemann, M. L. Gabriele, K. A. Townsend, K. R. Sung, J. S. Duker, J. G. Fujimoto, and J. S. Schuman, “Three-dimensional optical coherence tomography (3D-OCT) image enhancement with segmentation-free contour modeling C-mode,” Invest. Ophthalmol. Vis. Sci. 50(3), 1344–1349 (2009).
[Crossref] [PubMed]

Kardon, R.

M. K. Garvin, M. D. Abramoff, R. Kardon, S. R. Russell, X. Wu, and M. Sonka, “Intraretinal layer segmentation of macular optical coherence tomography images using optimal 3-D graph search,” IEEE Trans. Med. Imaging 27(10), 1495–1505 (2008).
[Crossref] [PubMed]

Keane, P. A.

P. A. Keane, P. S. Mand, S. Liakopoulos, A. C. Walsh, and S. R. Sadda, “Accuracy of retinal thickness measurements obtained with Cirrus optical coherence tomography,” Br. J. Ophthalmol. 93(11), 1461–1467 (2009).
[Crossref] [PubMed]

Khanifar, A. A.

N. Jain, S. Farsiu, A. A. Khanifar, S. Bearelly, R. T. Smith, J. A. Izatt, and C. A. Toth, “Quantitative comparison of drusen segmented on SD-OCT versus drusen delineated on color fundus photographs,” Invest. Ophthalmol. Vis. Sci. 51(10), 4875–4883 (2010).
[Crossref] [PubMed]

Kim, J.

H. Ishikawa, J. Kim, T. R. Friberg, G. Wollstein, L. Kagemann, M. L. Gabriele, K. A. Townsend, K. R. Sung, J. S. Duker, J. G. Fujimoto, and J. S. Schuman, “Three-dimensional optical coherence tomography (3D-OCT) image enhancement with segmentation-free contour modeling C-mode,” Invest. Ophthalmol. Vis. Sci. 50(3), 1344–1349 (2009).
[Crossref] [PubMed]

Kim, J. Y.

H. J. Lee, M. S. Kim, Y. J. Jo, and J. Y. Kim, “Ganglion cell–inner plexiform layer thickness in retinal diseases: Repeatability study of spectral-domain optical coherence tomography,” Am. J. Ophthalmol. 160(2), 283–289 (2015).
[Crossref] [PubMed]

H. J. Lee, M. S. Kim, Y. J. Jo, and J. Y. Kim, “Thickness of the macula, retinal nerve fiber layer, and ganglion cell layer in the epiretinal membrane: The repeatability study of optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 56(8), 4554–4559 (2015).
[Crossref] [PubMed]

Kim, M. S.

H. J. Lee, M. S. Kim, Y. J. Jo, and J. Y. Kim, “Thickness of the macula, retinal nerve fiber layer, and ganglion cell layer in the epiretinal membrane: The repeatability study of optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 56(8), 4554–4559 (2015).
[Crossref] [PubMed]

H. J. Lee, M. S. Kim, Y. J. Jo, and J. Y. Kim, “Ganglion cell–inner plexiform layer thickness in retinal diseases: Repeatability study of spectral-domain optical coherence tomography,” Am. J. Ophthalmol. 160(2), 283–289 (2015).
[Crossref] [PubMed]

Kim, Y. D.

J. R. Lee, J. W. Jeoung, J. Choi, J. Y. Choi, K. H. Park, and Y. D. Kim, “Structure-function relationships in normal and glaucomatous eyes determined by time- and spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6424–6430 (2010).
[Crossref] [PubMed]

Klein, R.

F. L. Ferris, M. D. Davis, T. E. Clemons, L. Y. Lee, E. Y. Chew, A. S. Lindblad, R. C. Milton, S. B. Bressler, R. Klein, and Age-Related Eye Disease Study (AREDS) Research Group, “A simplified severity scale for age-related macular degeneration: AREDS Report No. 18,” Arch. Ophthalmol. 123(11), 1570–1574 (2005).
[Crossref] [PubMed]

Kowal, J.

P. A. Dufour, L. Ceklic, H. Abdillahi, S. Schröder, S. De Dzanet, U. Wolf-Schnurrbusch, and J. Kowal, “Graph-based multi-surface segmentation of OCT data using trained hard and soft constraints,” IEEE Trans. Med. Imaging 32(3), 531–543 (2013).
[Crossref] [PubMed]

Kuo, A. N.

L. Fang, S. Li, R. P. McNabb, Q. Nie, A. N. Kuo, C. A. Toth, J. A. Izatt, and S. Farsiu, “Fast acquisition and reconstruction of optical coherence tomography images via sparse representation,” IEEE Trans. Med. Imaging 32(11), 2034–2049 (2013).
[Crossref] [PubMed]

Kutzscher, L.

Q. Chen, T. Leng, L. Zheng, L. Kutzscher, J. Ma, L. de Sisternes, and D. L. Rubin, “Automated drusen segmentation and quantification in SD-OCT images,” Med. Image Anal. 17(8), 1058–1072 (2013).
[Crossref] [PubMed]

Lang, A.

Lee, H. J.

H. J. Lee, M. S. Kim, Y. J. Jo, and J. Y. Kim, “Thickness of the macula, retinal nerve fiber layer, and ganglion cell layer in the epiretinal membrane: The repeatability study of optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 56(8), 4554–4559 (2015).
[Crossref] [PubMed]

H. J. Lee, M. S. Kim, Y. J. Jo, and J. Y. Kim, “Ganglion cell–inner plexiform layer thickness in retinal diseases: Repeatability study of spectral-domain optical coherence tomography,” Am. J. Ophthalmol. 160(2), 283–289 (2015).
[Crossref] [PubMed]

Lee, J. R.

J. R. Lee, J. W. Jeoung, J. Choi, J. Y. Choi, K. H. Park, and Y. D. Kim, “Structure-function relationships in normal and glaucomatous eyes determined by time- and spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6424–6430 (2010).
[Crossref] [PubMed]

Lee, K.

G. Quellec, K. Lee, M. Dolejsi, M. K. Garvin, M. D. Abràmoff, and M. Sonka, “Three-dimensional analysis of retinal layer texture: identification of fluid-filled regions in SD-OCT of the macula,” IEEE Trans. Med. Imaging 29(6), 1321–1330 (2010).
[Crossref] [PubMed]

Lee, L. Y.

F. L. Ferris, M. D. Davis, T. E. Clemons, L. Y. Lee, E. Y. Chew, A. S. Lindblad, R. C. Milton, S. B. Bressler, R. Klein, and Age-Related Eye Disease Study (AREDS) Research Group, “A simplified severity scale for age-related macular degeneration: AREDS Report No. 18,” Arch. Ophthalmol. 123(11), 1570–1574 (2005).
[Crossref] [PubMed]

Lee, S. Y.

S. Y. Lee, P. F. Stetson, H. Ruiz-Garcia, F. M. Heussen, and S. R. Sadda, “Automated characterization of pigment epithelial detachment by optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53(1), 164–170 (2012).
[Crossref] [PubMed]

Lemij, H. G.

Leng, T.

L. de Sisternes, J. Hu, D. L. Rubin, and T. Leng, “Visual prognosis of eyes recovering from macular hole surgery through automated quantitative analysis of spectral-domain optical coherence tomography (SD-OCT) scans,” Invest. Ophthalmol. Vis. Sci. 56(8), 4631–4643 (2015).
[Crossref] [PubMed]

L. de Sisternes, N. Simon, R. Tibshirani, T. Leng, and D. L. Rubin, “Quantitative SD-OCT imaging biomarkers as indicators of age-related macular degeneration progression,” Invest. Ophthalmol. Vis. Sci. 55(11), 7093–7103 (2014).
[Crossref] [PubMed]

Q. Chen, T. Leng, L. Zheng, L. Kutzscher, J. Ma, L. de Sisternes, and D. L. Rubin, “Automated drusen segmentation and quantification in SD-OCT images,” Med. Image Anal. 17(8), 1058–1072 (2013).
[Crossref] [PubMed]

Li, K.

K. Li, X. Wu, D. Z. Chen, and M. Sonka, “Optimal surface segmentation in volumetric images--a graph-theoretic approach,” IEEE Trans. Pattern Anal. Mach. Intell. 28(1), 119–134 (2006).
[Crossref] [PubMed]

Li, S.

L. Fang, S. Li, R. P. McNabb, Q. Nie, A. N. Kuo, C. A. Toth, J. A. Izatt, and S. Farsiu, “Fast acquisition and reconstruction of optical coherence tomography images via sparse representation,” IEEE Trans. Med. Imaging 32(11), 2034–2049 (2013).
[Crossref] [PubMed]

Li, X. T.

Liakopoulos, S.

P. A. Keane, P. S. Mand, S. Liakopoulos, A. C. Walsh, and S. R. Sadda, “Accuracy of retinal thickness measurements obtained with Cirrus optical coherence tomography,” Br. J. Ophthalmol. 93(11), 1461–1467 (2009).
[Crossref] [PubMed]

Liebmann, J. M.

H. Ishikawa, S. Piette, J. M. Liebmann, and R. Ritch, “Detecting the inner and outer borders of the retinal nerve fiber layer using optical coherence tomography,” Graefes Arch. Clin. Exp. Ophthalmol. 240(5), 362–371 (2002).
[Crossref] [PubMed]

Lin, C. P.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Lindblad, A. S.

F. L. Ferris, M. D. Davis, T. E. Clemons, L. Y. Lee, E. Y. Chew, A. S. Lindblad, R. C. Milton, S. B. Bressler, R. Klein, and Age-Related Eye Disease Study (AREDS) Research Group, “A simplified severity scale for age-related macular degeneration: AREDS Report No. 18,” Arch. Ophthalmol. 123(11), 1570–1574 (2005).
[Crossref] [PubMed]

Lorenz, B.

A. Ehnes, Y. Wenner, C. Friedburg, M. N. Preising, W. Bowl, W. Sekundo, E. M. Zu Bexten, K. Stieger, and B. Lorenz, “Optical coherence tomography (OCT) device independent intraretinal layer segmentation,” Transl. Vis. Sci. Technol. 3(1), 1–16 (2014).
[Crossref] [PubMed]

Ma, J.

Q. Chen, T. Leng, L. Zheng, L. Kutzscher, J. Ma, L. de Sisternes, and D. L. Rubin, “Automated drusen segmentation and quantification in SD-OCT images,” Med. Image Anal. 17(8), 1058–1072 (2013).
[Crossref] [PubMed]

Mand, P. S.

P. A. Keane, P. S. Mand, S. Liakopoulos, A. C. Walsh, and S. R. Sadda, “Accuracy of retinal thickness measurements obtained with Cirrus optical coherence tomography,” Br. J. Ophthalmol. 93(11), 1461–1467 (2009).
[Crossref] [PubMed]

Mardin, C. Y.

Marmor, M. F.

L. de Sisternes, J. Hu, D. L. Rubin, and M. F. Marmor, “Localization of damage in progressive hydroxychloroquine retinopathy on and off the drug: inner versus outer retina, parafovea versus peripheral fovea,” Invest. Ophthalmol. Vis. Sci. 56(5), 3415–3426 (2015).
[Crossref] [PubMed]

Matt, G.

G. Matt, S. Sacu, W. Buehl, C. Ahlers, R. Dunavoelgyi, C. Pruente, and U. Schmidt-Erfurth, “Comparison of retinal thickness values and segmentation performance of different OCT devices in acute branch retinal vein occlusion,” Eye (Lond.) 25(4), 511–518 (2011).
[Crossref] [PubMed]

Mayer, M. A.

McNabb, R. P.

L. Fang, S. Li, R. P. McNabb, Q. Nie, A. N. Kuo, C. A. Toth, J. A. Izatt, and S. Farsiu, “Fast acquisition and reconstruction of optical coherence tomography images via sparse representation,” IEEE Trans. Med. Imaging 32(11), 2034–2049 (2013).
[Crossref] [PubMed]

Mettu, P. S.

Miller, J. W.

K. Yi, M. Mujat, B. H. Park, W. Sun, J. W. Miller, J. M. Seddon, L. H. Young, J. F. de Boer, and T. C. Chen, “Spectral domain optical coherence tomography for quantitative evaluation of drusen and associated structural changes in non-neovascular age-related macular degeneration,” Br. J. Ophthalmol. 93(2), 176–181 (2009).
[Crossref] [PubMed]

Milton, R. C.

F. L. Ferris, M. D. Davis, T. E. Clemons, L. Y. Lee, E. Y. Chew, A. S. Lindblad, R. C. Milton, S. B. Bressler, R. Klein, and Age-Related Eye Disease Study (AREDS) Research Group, “A simplified severity scale for age-related macular degeneration: AREDS Report No. 18,” Arch. Ophthalmol. 123(11), 1570–1574 (2005).
[Crossref] [PubMed]

Mishra, A.

Morel, J. M.

A. Buades, B. Coll, and J. M. Morel, “The staircasing effect in neighborhood filters and its solution,” IEEE Trans. Image Process. 15(6), 1499–1505 (2006).
[Crossref] [PubMed]

A. Buades, B. Coll, and J. M. Morel, “A non-local algorithm for image denoising,” Comput. Vis. Patt. Recog. 2(7), 60–65 (2005).

Mujat, M.

K. Yi, M. Mujat, B. H. Park, W. Sun, J. W. Miller, J. M. Seddon, L. H. Young, J. F. de Boer, and T. C. Chen, “Spectral domain optical coherence tomography for quantitative evaluation of drusen and associated structural changes in non-neovascular age-related macular degeneration,” Br. J. Ophthalmol. 93(2), 176–181 (2009).
[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]

Neuvo, Y.

L. Yin, R. K. Yang, M. Gabbouj, and Y. Neuvo, “Weighted median filters: A tutorial,” IEEE Trans. Circuits Syst. II Analog Digit. Siganl Process. 43(3), 157–192 (1996).
[Crossref]

Nicholas, P.

Nie, Q.

L. Fang, S. Li, R. P. McNabb, Q. Nie, A. N. Kuo, C. A. Toth, J. A. Izatt, and S. Farsiu, “Fast acquisition and reconstruction of optical coherence tomography images via sparse representation,” IEEE Trans. Med. Imaging 32(11), 2034–2049 (2013).
[Crossref] [PubMed]

O’Connell, R. V.

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, C. A. Toth, and Age-Related Eye Disease Study 2 Ancillary Spectral Domain Optical Coherence Tomography Study Group, “Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography,” Ophthalmology 121(1), 162–172 (2014).
[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]

Park, B.

Park, B. H.

K. Yi, M. Mujat, B. H. Park, W. Sun, J. W. Miller, J. M. Seddon, L. H. Young, J. F. de Boer, and T. C. Chen, “Spectral domain optical coherence tomography for quantitative evaluation of drusen and associated structural changes in non-neovascular age-related macular degeneration,” Br. J. Ophthalmol. 93(2), 176–181 (2009).
[Crossref] [PubMed]

Park, K. H.

J. R. Lee, J. W. Jeoung, J. Choi, J. Y. Choi, K. H. Park, and Y. D. Kim, “Structure-function relationships in normal and glaucomatous eyes determined by time- and spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6424–6430 (2010).
[Crossref] [PubMed]

Parrilli, S.

S. Parrilli, M. Poderico, C. V. Angelino, G. Scarpa, and L. Verdoliva, “A non local approach for SAR image denoising,” IEEE Geoscience and Remote Sensing Symposium (IGARSS) (2010).

Piette, S.

H. Ishikawa, S. Piette, J. M. Liebmann, and R. Ritch, “Detecting the inner and outer borders of the retinal nerve fiber layer using optical coherence tomography,” Graefes Arch. Clin. Exp. Ophthalmol. 240(5), 362–371 (2002).
[Crossref] [PubMed]

Poderico, M.

S. Parrilli, M. Poderico, C. V. Angelino, G. Scarpa, and L. Verdoliva, “A non local approach for SAR image denoising,” IEEE Geoscience and Remote Sensing Symposium (IGARSS) (2010).

Preising, M. N.

A. Ehnes, Y. Wenner, C. Friedburg, M. N. Preising, W. Bowl, W. Sekundo, E. M. Zu Bexten, K. Stieger, and B. Lorenz, “Optical coherence tomography (OCT) device independent intraretinal layer segmentation,” Transl. Vis. Sci. Technol. 3(1), 1–16 (2014).
[Crossref] [PubMed]

Prince, J. L.

Pruente, C.

G. Matt, S. Sacu, W. Buehl, C. Ahlers, R. Dunavoelgyi, C. Pruente, and U. Schmidt-Erfurth, “Comparison of retinal thickness values and segmentation performance of different OCT devices in acute branch retinal vein occlusion,” Eye (Lond.) 25(4), 511–518 (2011).
[Crossref] [PubMed]

Puliafito, C. A.

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]

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Quellec, G.

G. Quellec, K. Lee, M. Dolejsi, M. K. Garvin, M. D. Abràmoff, and M. Sonka, “Three-dimensional analysis of retinal layer texture: identification of fluid-filled regions in SD-OCT of the macula,” IEEE Trans. Med. Imaging 29(6), 1321–1330 (2010).
[Crossref] [PubMed]

Rabbani, H.

R. Kafieh, H. Rabbani, M. D. Abramoff, and M. Sonka, “Intra-retinal layer segmentation of 3D optical coherence tomography using coarse grained diffusion map,” Med. Image Anal. 17(8), 907–928 (2013).
[Crossref] [PubMed]

Ritch, R.

H. Ishikawa, S. Piette, J. M. Liebmann, and R. Ritch, “Detecting the inner and outer borders of the retinal nerve fiber layer using optical coherence tomography,” Graefes Arch. Clin. Exp. Ophthalmol. 240(5), 362–371 (2002).
[Crossref] [PubMed]

Rodriguez, M.

F. G. Schlanitz, C. Ahlers, S. Sacu, C. Schütze, M. Rodriguez, S. Schriefl, I. Golbaz, T. Spalek, G. Stock, and U. Schmidt-Erfurth, “Performance of drusen detection by spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6715–6721 (2010).
[Crossref] [PubMed]

Rubin, D. L.

L. de Sisternes, J. Hu, D. L. Rubin, and M. F. Marmor, “Localization of damage in progressive hydroxychloroquine retinopathy on and off the drug: inner versus outer retina, parafovea versus peripheral fovea,” Invest. Ophthalmol. Vis. Sci. 56(5), 3415–3426 (2015).
[Crossref] [PubMed]

L. de Sisternes, J. Hu, D. L. Rubin, and T. Leng, “Visual prognosis of eyes recovering from macular hole surgery through automated quantitative analysis of spectral-domain optical coherence tomography (SD-OCT) scans,” Invest. Ophthalmol. Vis. Sci. 56(8), 4631–4643 (2015).
[Crossref] [PubMed]

L. de Sisternes, N. Simon, R. Tibshirani, T. Leng, and D. L. Rubin, “Quantitative SD-OCT imaging biomarkers as indicators of age-related macular degeneration progression,” Invest. Ophthalmol. Vis. Sci. 55(11), 7093–7103 (2014).
[Crossref] [PubMed]

Q. Chen, T. Leng, L. Zheng, L. Kutzscher, J. Ma, L. de Sisternes, and D. L. Rubin, “Automated drusen segmentation and quantification in SD-OCT images,” Med. Image Anal. 17(8), 1058–1072 (2013).
[Crossref] [PubMed]

Ruiz-Garcia, H.

S. Y. Lee, P. F. Stetson, H. Ruiz-Garcia, F. M. Heussen, and S. R. Sadda, “Automated characterization of pigment epithelial detachment by optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53(1), 164–170 (2012).
[Crossref] [PubMed]

Russell, S. R.

M. K. Garvin, M. D. Abràmoff, X. Wu, S. R. Russell, T. L. Burns, and M. Sonka, “Automated 3-D intraretinal layer segmentation of macular spectral-domain optical coherence tomography images,” IEEE Trans. Med. Imaging 28(9), 1436–1447 (2009).
[Crossref] [PubMed]

M. K. Garvin, M. D. Abramoff, R. Kardon, S. R. Russell, X. Wu, and M. Sonka, “Intraretinal layer segmentation of macular optical coherence tomography images using optimal 3-D graph search,” IEEE Trans. Med. Imaging 27(10), 1495–1505 (2008).
[Crossref] [PubMed]

Sacu, S.

G. Matt, S. Sacu, W. Buehl, C. Ahlers, R. Dunavoelgyi, C. Pruente, and U. Schmidt-Erfurth, “Comparison of retinal thickness values and segmentation performance of different OCT devices in acute branch retinal vein occlusion,” Eye (Lond.) 25(4), 511–518 (2011).
[Crossref] [PubMed]

F. G. Schlanitz, C. Ahlers, S. Sacu, C. Schütze, M. Rodriguez, S. Schriefl, I. Golbaz, T. Spalek, G. Stock, and U. Schmidt-Erfurth, “Performance of drusen detection by spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6715–6721 (2010).
[Crossref] [PubMed]

Sadda, S.

G. Staurenghi, S. Sadda, U. Chakravarthy, R. F. Spaide, and International Nomenclature for Optical Coherence Tomography (IN•OCT) Panel, “Proposed lexicon for anatomic landmarks in normal posterior segment spectral-domain optical coherence tomography: the IN•OCT consensus,” Ophthalmology 121(8), 1572–1578 (2014).
[Crossref] [PubMed]

Sadda, S. R.

S. Y. Lee, P. F. Stetson, H. Ruiz-Garcia, F. M. Heussen, and S. R. Sadda, “Automated characterization of pigment epithelial detachment by optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53(1), 164–170 (2012).
[Crossref] [PubMed]

P. A. Keane, P. S. Mand, S. Liakopoulos, A. C. Walsh, and S. R. Sadda, “Accuracy of retinal thickness measurements obtained with Cirrus optical coherence tomography,” Br. J. Ophthalmol. 93(11), 1461–1467 (2009).
[Crossref] [PubMed]

Salinas, H. M.

Scarpa, G.

S. Parrilli, M. Poderico, C. V. Angelino, G. Scarpa, and L. Verdoliva, “A non local approach for SAR image denoising,” IEEE Geoscience and Remote Sensing Symposium (IGARSS) (2010).

Schlanitz, F. G.

F. G. Schlanitz, C. Ahlers, S. Sacu, C. Schütze, M. Rodriguez, S. Schriefl, I. Golbaz, T. Spalek, G. Stock, and U. Schmidt-Erfurth, “Performance of drusen detection by spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6715–6721 (2010).
[Crossref] [PubMed]

Schmidt-Erfurth, U.

G. Matt, S. Sacu, W. Buehl, C. Ahlers, R. Dunavoelgyi, C. Pruente, and U. Schmidt-Erfurth, “Comparison of retinal thickness values and segmentation performance of different OCT devices in acute branch retinal vein occlusion,” Eye (Lond.) 25(4), 511–518 (2011).
[Crossref] [PubMed]

F. G. Schlanitz, C. Ahlers, S. Sacu, C. Schütze, M. Rodriguez, S. Schriefl, I. Golbaz, T. Spalek, G. Stock, and U. Schmidt-Erfurth, “Performance of drusen detection by spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6715–6721 (2010).
[Crossref] [PubMed]

C. Ahlers, C. Simader, W. Geitzenauer, G. Stock, P. Stetson, S. Dastmalchi, and U. Schmidt-Erfurth, “Automatic segmentation in three-dimensional analysis of fibrovascular pigmentepithelial detachment using high-definition optical coherence tomography,” Br. J. Ophthalmol. 92(2), 197–203 (2008).
[Crossref] [PubMed]

Schriefl, S.

F. G. Schlanitz, C. Ahlers, S. Sacu, C. Schütze, M. Rodriguez, S. Schriefl, I. Golbaz, T. Spalek, G. Stock, and U. Schmidt-Erfurth, “Performance of drusen detection by spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6715–6721 (2010).
[Crossref] [PubMed]

Schröder, S.

P. A. Dufour, L. Ceklic, H. Abdillahi, S. Schröder, S. De Dzanet, U. Wolf-Schnurrbusch, and J. Kowal, “Graph-based multi-surface segmentation of OCT data using trained hard and soft constraints,” IEEE Trans. Med. Imaging 32(3), 531–543 (2013).
[Crossref] [PubMed]

Schuman, J. S.

H. Ishikawa, J. Kim, T. R. Friberg, G. Wollstein, L. Kagemann, M. L. Gabriele, K. A. Townsend, K. R. Sung, J. S. Duker, J. G. Fujimoto, and J. S. Schuman, “Three-dimensional optical coherence tomography (3D-OCT) image enhancement with segmentation-free contour modeling C-mode,” Invest. Ophthalmol. Vis. Sci. 50(3), 1344–1349 (2009).
[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]

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Schütze, C.

F. G. Schlanitz, C. Ahlers, S. Sacu, C. Schütze, M. Rodriguez, S. Schriefl, I. Golbaz, T. Spalek, G. Stock, and U. Schmidt-Erfurth, “Performance of drusen detection by spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6715–6721 (2010).
[Crossref] [PubMed]

Seddon, J. M.

K. Yi, M. Mujat, B. H. Park, W. Sun, J. W. Miller, J. M. Seddon, L. H. Young, J. F. de Boer, and T. C. Chen, “Spectral domain optical coherence tomography for quantitative evaluation of drusen and associated structural changes in non-neovascular age-related macular degeneration,” Br. J. Ophthalmol. 93(2), 176–181 (2009).
[Crossref] [PubMed]

Sekundo, W.

A. Ehnes, Y. Wenner, C. Friedburg, M. N. Preising, W. Bowl, W. Sekundo, E. M. Zu Bexten, K. Stieger, and B. Lorenz, “Optical coherence tomography (OCT) device independent intraretinal layer segmentation,” Transl. Vis. Sci. Technol. 3(1), 1–16 (2014).
[Crossref] [PubMed]

Simader, C.

C. Ahlers, C. Simader, W. Geitzenauer, G. Stock, P. Stetson, S. Dastmalchi, and U. Schmidt-Erfurth, “Automatic segmentation in three-dimensional analysis of fibrovascular pigmentepithelial detachment using high-definition optical coherence tomography,” Br. J. Ophthalmol. 92(2), 197–203 (2008).
[Crossref] [PubMed]

Simon, N.

L. de Sisternes, N. Simon, R. Tibshirani, T. Leng, and D. L. Rubin, “Quantitative SD-OCT imaging biomarkers as indicators of age-related macular degeneration progression,” Invest. Ophthalmol. Vis. Sci. 55(11), 7093–7103 (2014).
[Crossref] [PubMed]

Smith, R. T.

J. H. Acton, R. T. Smith, D. C. Hood, and V. C. Greenstein, “Relationship between retinal layer thickness and the visual field in early age-related macular degeneration,” Invest. Ophthalmol. Vis. Sci. 53(12), 7618–7624 (2012).
[Crossref] [PubMed]

N. Jain, S. Farsiu, A. A. Khanifar, S. Bearelly, R. T. Smith, J. A. Izatt, and C. A. Toth, “Quantitative comparison of drusen segmented on SD-OCT versus drusen delineated on color fundus photographs,” Invest. Ophthalmol. Vis. Sci. 51(10), 4875–4883 (2010).
[Crossref] [PubMed]

Sonka, M.

R. Kafieh, H. Rabbani, M. D. Abramoff, and M. Sonka, “Intra-retinal layer segmentation of 3D optical coherence tomography using coarse grained diffusion map,” Med. Image Anal. 17(8), 907–928 (2013).
[Crossref] [PubMed]

G. Quellec, K. Lee, M. Dolejsi, M. K. Garvin, M. D. Abràmoff, and M. Sonka, “Three-dimensional analysis of retinal layer texture: identification of fluid-filled regions in SD-OCT of the macula,” IEEE Trans. Med. Imaging 29(6), 1321–1330 (2010).
[Crossref] [PubMed]

M. K. Garvin, M. D. Abràmoff, X. Wu, S. R. Russell, T. L. Burns, and M. Sonka, “Automated 3-D intraretinal layer segmentation of macular spectral-domain optical coherence tomography images,” IEEE Trans. Med. Imaging 28(9), 1436–1447 (2009).
[Crossref] [PubMed]

M. K. Garvin, M. D. Abramoff, R. Kardon, S. R. Russell, X. Wu, and M. Sonka, “Intraretinal layer segmentation of macular optical coherence tomography images using optimal 3-D graph search,” IEEE Trans. Med. Imaging 27(10), 1495–1505 (2008).
[Crossref] [PubMed]

K. Li, X. Wu, D. Z. Chen, and M. Sonka, “Optimal surface segmentation in volumetric images--a graph-theoretic approach,” IEEE Trans. Pattern Anal. Mach. Intell. 28(1), 119–134 (2006).
[Crossref] [PubMed]

Sotirchos, E. S.

Spaide, R. F.

G. Staurenghi, S. Sadda, U. Chakravarthy, R. F. Spaide, and International Nomenclature for Optical Coherence Tomography (IN•OCT) Panel, “Proposed lexicon for anatomic landmarks in normal posterior segment spectral-domain optical coherence tomography: the IN•OCT consensus,” Ophthalmology 121(8), 1572–1578 (2014).
[Crossref] [PubMed]

Spalek, T.

F. G. Schlanitz, C. Ahlers, S. Sacu, C. Schütze, M. Rodriguez, S. Schriefl, I. Golbaz, T. Spalek, G. Stock, and U. Schmidt-Erfurth, “Performance of drusen detection by spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6715–6721 (2010).
[Crossref] [PubMed]

Staurenghi, G.

G. Staurenghi, S. Sadda, U. Chakravarthy, R. F. Spaide, and International Nomenclature for Optical Coherence Tomography (IN•OCT) Panel, “Proposed lexicon for anatomic landmarks in normal posterior segment spectral-domain optical coherence tomography: the IN•OCT consensus,” Ophthalmology 121(8), 1572–1578 (2014).
[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]

Stetson, P.

C. Ahlers, C. Simader, W. Geitzenauer, G. Stock, P. Stetson, S. Dastmalchi, and U. Schmidt-Erfurth, “Automatic segmentation in three-dimensional analysis of fibrovascular pigmentepithelial detachment using high-definition optical coherence tomography,” Br. J. Ophthalmol. 92(2), 197–203 (2008).
[Crossref] [PubMed]

Stetson, P. F.

S. Y. Lee, P. F. Stetson, H. Ruiz-Garcia, F. M. Heussen, and S. R. Sadda, “Automated characterization of pigment epithelial detachment by optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53(1), 164–170 (2012).
[Crossref] [PubMed]

Stieger, K.

A. Ehnes, Y. Wenner, C. Friedburg, M. N. Preising, W. Bowl, W. Sekundo, E. M. Zu Bexten, K. Stieger, and B. Lorenz, “Optical coherence tomography (OCT) device independent intraretinal layer segmentation,” Transl. Vis. Sci. Technol. 3(1), 1–16 (2014).
[Crossref] [PubMed]

Stinson, W. G.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Stock, G.

F. G. Schlanitz, C. Ahlers, S. Sacu, C. Schütze, M. Rodriguez, S. Schriefl, I. Golbaz, T. Spalek, G. Stock, and U. Schmidt-Erfurth, “Performance of drusen detection by spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6715–6721 (2010).
[Crossref] [PubMed]

C. Ahlers, C. Simader, W. Geitzenauer, G. Stock, P. Stetson, S. Dastmalchi, and U. Schmidt-Erfurth, “Automatic segmentation in three-dimensional analysis of fibrovascular pigmentepithelial detachment using high-definition optical coherence tomography,” Br. J. Ophthalmol. 92(2), 197–203 (2008).
[Crossref] [PubMed]

Sun, W.

K. Yi, M. Mujat, B. H. Park, W. Sun, J. W. Miller, J. M. Seddon, L. H. Young, J. F. de Boer, and T. C. Chen, “Spectral domain optical coherence tomography for quantitative evaluation of drusen and associated structural changes in non-neovascular age-related macular degeneration,” Br. J. Ophthalmol. 93(2), 176–181 (2009).
[Crossref] [PubMed]

Sung, K. R.

H. Ishikawa, J. Kim, T. R. Friberg, G. Wollstein, L. Kagemann, M. L. Gabriele, K. A. Townsend, K. R. Sung, J. S. Duker, J. G. Fujimoto, and J. S. Schuman, “Three-dimensional optical coherence tomography (3D-OCT) image enhancement with segmentation-free contour modeling C-mode,” Invest. Ophthalmol. Vis. Sci. 50(3), 1344–1349 (2009).
[Crossref] [PubMed]

Swanson, E. A.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Tibshirani, R.

L. de Sisternes, N. Simon, R. Tibshirani, T. Leng, and D. L. Rubin, “Quantitative SD-OCT imaging biomarkers as indicators of age-related macular degeneration progression,” Invest. Ophthalmol. Vis. Sci. 55(11), 7093–7103 (2014).
[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, C. A. Toth, and Age-Related Eye Disease Study 2 Ancillary Spectral Domain Optical Coherence Tomography Study Group, “Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography,” Ophthalmology 121(1), 162–172 (2014).
[Crossref] [PubMed]

L. Fang, S. Li, R. P. McNabb, Q. Nie, A. N. Kuo, C. A. Toth, J. A. Izatt, and S. Farsiu, “Fast acquisition and reconstruction of optical coherence tomography images via sparse representation,” IEEE Trans. Med. Imaging 32(11), 2034–2049 (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, 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]

N. Jain, S. Farsiu, A. A. Khanifar, S. Bearelly, R. T. Smith, J. A. Izatt, and C. A. Toth, “Quantitative comparison of drusen segmented on SD-OCT versus drusen delineated on color fundus photographs,” Invest. Ophthalmol. Vis. Sci. 51(10), 4875–4883 (2010).
[Crossref] [PubMed]

Townsend, K. A.

H. Ishikawa, J. Kim, T. R. Friberg, G. Wollstein, L. Kagemann, M. L. Gabriele, K. A. Townsend, K. R. Sung, J. S. Duker, J. G. Fujimoto, and J. S. Schuman, “Three-dimensional optical coherence tomography (3D-OCT) image enhancement with segmentation-free contour modeling C-mode,” Invest. Ophthalmol. Vis. Sci. 50(3), 1344–1349 (2009).
[Crossref] [PubMed]

van der Schoot, J.

Verdoliva, L.

S. Parrilli, M. Poderico, C. V. Angelino, G. Scarpa, and L. Verdoliva, “A non local approach for SAR image denoising,” IEEE Geoscience and Remote Sensing Symposium (IGARSS) (2010).

Vermeer, K. A.

Walsh, A. C.

P. A. Keane, P. S. Mand, S. Liakopoulos, A. C. Walsh, and S. R. Sadda, “Accuracy of retinal thickness measurements obtained with Cirrus optical coherence tomography,” Br. J. Ophthalmol. 93(11), 1461–1467 (2009).
[Crossref] [PubMed]

Wenner, Y.

A. Ehnes, Y. Wenner, C. Friedburg, M. N. Preising, W. Bowl, W. Sekundo, E. M. Zu Bexten, K. Stieger, and B. Lorenz, “Optical coherence tomography (OCT) device independent intraretinal layer segmentation,” Transl. Vis. Sci. Technol. 3(1), 1–16 (2014).
[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]

Wolf-Schnurrbusch, U.

P. A. Dufour, L. Ceklic, H. Abdillahi, S. Schröder, S. De Dzanet, U. Wolf-Schnurrbusch, and J. Kowal, “Graph-based multi-surface segmentation of OCT data using trained hard and soft constraints,” IEEE Trans. Med. Imaging 32(3), 531–543 (2013).
[Crossref] [PubMed]

Wollstein, G.

H. Ishikawa, J. Kim, T. R. Friberg, G. Wollstein, L. Kagemann, M. L. Gabriele, K. A. Townsend, K. R. Sung, J. S. Duker, J. G. Fujimoto, and J. S. Schuman, “Three-dimensional optical coherence tomography (3D-OCT) image enhancement with segmentation-free contour modeling C-mode,” Invest. Ophthalmol. Vis. Sci. 50(3), 1344–1349 (2009).
[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]

Wong, A.

Wong, M. A.

J. A. Hartigan and M. A. Wong, “Algorithm AS 136: A K-means clustering algorithm,” J. R. Stat. Soc. Series C 28(1), 100–108 (1979).

Wu, X.

M. K. Garvin, M. D. Abràmoff, X. Wu, S. R. Russell, T. L. Burns, and M. Sonka, “Automated 3-D intraretinal layer segmentation of macular spectral-domain optical coherence tomography images,” IEEE Trans. Med. Imaging 28(9), 1436–1447 (2009).
[Crossref] [PubMed]

M. K. Garvin, M. D. Abramoff, R. Kardon, S. R. Russell, X. Wu, and M. Sonka, “Intraretinal layer segmentation of macular optical coherence tomography images using optimal 3-D graph search,” IEEE Trans. Med. Imaging 27(10), 1495–1505 (2008).
[Crossref] [PubMed]

K. Li, X. Wu, D. Z. Chen, and M. Sonka, “Optimal surface segmentation in volumetric images--a graph-theoretic approach,” IEEE Trans. Pattern Anal. Mach. Intell. 28(1), 119–134 (2006).
[Crossref] [PubMed]

Yang, R. K.

L. Yin, R. K. Yang, M. Gabbouj, and Y. Neuvo, “Weighted median filters: A tutorial,” IEEE Trans. Circuits Syst. II Analog Digit. Siganl Process. 43(3), 157–192 (1996).
[Crossref]

Yi, K.

K. Yi, M. Mujat, B. H. Park, W. Sun, J. W. Miller, J. M. Seddon, L. H. Young, J. F. de Boer, and T. C. Chen, “Spectral domain optical coherence tomography for quantitative evaluation of drusen and associated structural changes in non-neovascular age-related macular degeneration,” Br. J. Ophthalmol. 93(2), 176–181 (2009).
[Crossref] [PubMed]

Yin, L.

L. Yin, R. K. Yang, M. Gabbouj, and Y. Neuvo, “Weighted median filters: A tutorial,” IEEE Trans. Circuits Syst. II Analog Digit. Siganl Process. 43(3), 157–192 (1996).
[Crossref]

Ying, H. S.

Young, L. H.

K. Yi, M. Mujat, B. H. Park, W. Sun, J. W. Miller, J. M. Seddon, L. H. Young, J. F. de Boer, and T. C. Chen, “Spectral domain optical coherence tomography for quantitative evaluation of drusen and associated structural changes in non-neovascular age-related macular degeneration,” Br. J. Ophthalmol. 93(2), 176–181 (2009).
[Crossref] [PubMed]

Yuan, E.

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, C. A. Toth, and Age-Related Eye Disease Study 2 Ancillary Spectral Domain Optical Coherence Tomography Study Group, “Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography,” Ophthalmology 121(1), 162–172 (2014).
[Crossref] [PubMed]

Zheng, L.

Q. Chen, T. Leng, L. Zheng, L. Kutzscher, J. Ma, L. de Sisternes, and D. L. Rubin, “Automated drusen segmentation and quantification in SD-OCT images,” Med. Image Anal. 17(8), 1058–1072 (2013).
[Crossref] [PubMed]

Zu Bexten, E. M.

A. Ehnes, Y. Wenner, C. Friedburg, M. N. Preising, W. Bowl, W. Sekundo, E. M. Zu Bexten, K. Stieger, and B. Lorenz, “Optical coherence tomography (OCT) device independent intraretinal layer segmentation,” Transl. Vis. Sci. Technol. 3(1), 1–16 (2014).
[Crossref] [PubMed]

Am. J. Ophthalmol. (1)

H. J. Lee, M. S. Kim, Y. J. Jo, and J. Y. Kim, “Ganglion cell–inner plexiform layer thickness in retinal diseases: Repeatability study of spectral-domain optical coherence tomography,” Am. J. Ophthalmol. 160(2), 283–289 (2015).
[Crossref] [PubMed]

Arch. Ophthalmol. (1)

F. L. Ferris, M. D. Davis, T. E. Clemons, L. Y. Lee, E. Y. Chew, A. S. Lindblad, R. C. Milton, S. B. Bressler, R. Klein, and Age-Related Eye Disease Study (AREDS) Research Group, “A simplified severity scale for age-related macular degeneration: AREDS Report No. 18,” Arch. Ophthalmol. 123(11), 1570–1574 (2005).
[Crossref] [PubMed]

Biomed. Opt. Express (4)

Br. J. Ophthalmol. (3)

K. Yi, M. Mujat, B. H. Park, W. Sun, J. W. Miller, J. M. Seddon, L. H. Young, J. F. de Boer, and T. C. Chen, “Spectral domain optical coherence tomography for quantitative evaluation of drusen and associated structural changes in non-neovascular age-related macular degeneration,” Br. J. Ophthalmol. 93(2), 176–181 (2009).
[Crossref] [PubMed]

C. Ahlers, C. Simader, W. Geitzenauer, G. Stock, P. Stetson, S. Dastmalchi, and U. Schmidt-Erfurth, “Automatic segmentation in three-dimensional analysis of fibrovascular pigmentepithelial detachment using high-definition optical coherence tomography,” Br. J. Ophthalmol. 92(2), 197–203 (2008).
[Crossref] [PubMed]

P. A. Keane, P. S. Mand, S. Liakopoulos, A. C. Walsh, and S. R. Sadda, “Accuracy of retinal thickness measurements obtained with Cirrus optical coherence tomography,” Br. J. Ophthalmol. 93(11), 1461–1467 (2009).
[Crossref] [PubMed]

Commun. Assoc. Comput. Machinery (1)

D. R. K. Brownrigg, “The weighted median filter,” Commun. Assoc. Comput. Machinery 27(8), 807–818 (1984).

Comput. Vis. Patt. Recog. (1)

A. Buades, B. Coll, and J. M. Morel, “A non-local algorithm for image denoising,” Comput. Vis. Patt. Recog. 2(7), 60–65 (2005).

Eye (Lond.) (1)

G. Matt, S. Sacu, W. Buehl, C. Ahlers, R. Dunavoelgyi, C. Pruente, and U. Schmidt-Erfurth, “Comparison of retinal thickness values and segmentation performance of different OCT devices in acute branch retinal vein occlusion,” Eye (Lond.) 25(4), 511–518 (2011).
[Crossref] [PubMed]

Graefes Arch. Clin. Exp. Ophthalmol. (1)

H. Ishikawa, S. Piette, J. M. Liebmann, and R. Ritch, “Detecting the inner and outer borders of the retinal nerve fiber layer using optical coherence tomography,” Graefes Arch. Clin. Exp. Ophthalmol. 240(5), 362–371 (2002).
[Crossref] [PubMed]

IEEE Trans. Circuits Syst. II Analog Digit. Siganl Process. (1)

L. Yin, R. K. Yang, M. Gabbouj, and Y. Neuvo, “Weighted median filters: A tutorial,” IEEE Trans. Circuits Syst. II Analog Digit. Siganl Process. 43(3), 157–192 (1996).
[Crossref]

IEEE Trans. Image Process. (1)

A. Buades, B. Coll, and J. M. Morel, “The staircasing effect in neighborhood filters and its solution,” IEEE Trans. Image Process. 15(6), 1499–1505 (2006).
[Crossref] [PubMed]

IEEE Trans. Med. Imaging (5)

M. K. Garvin, M. D. Abramoff, R. Kardon, S. R. Russell, X. Wu, and M. Sonka, “Intraretinal layer segmentation of macular optical coherence tomography images using optimal 3-D graph search,” IEEE Trans. Med. Imaging 27(10), 1495–1505 (2008).
[Crossref] [PubMed]

M. K. Garvin, M. D. Abràmoff, X. Wu, S. R. Russell, T. L. Burns, and M. Sonka, “Automated 3-D intraretinal layer segmentation of macular spectral-domain optical coherence tomography images,” IEEE Trans. Med. Imaging 28(9), 1436–1447 (2009).
[Crossref] [PubMed]

P. A. Dufour, L. Ceklic, H. Abdillahi, S. Schröder, S. De Dzanet, U. Wolf-Schnurrbusch, and J. Kowal, “Graph-based multi-surface segmentation of OCT data using trained hard and soft constraints,” IEEE Trans. Med. Imaging 32(3), 531–543 (2013).
[Crossref] [PubMed]

G. Quellec, K. Lee, M. Dolejsi, M. K. Garvin, M. D. Abràmoff, and M. Sonka, “Three-dimensional analysis of retinal layer texture: identification of fluid-filled regions in SD-OCT of the macula,” IEEE Trans. Med. Imaging 29(6), 1321–1330 (2010).
[Crossref] [PubMed]

L. Fang, S. Li, R. P. McNabb, Q. Nie, A. N. Kuo, C. A. Toth, J. A. Izatt, and S. Farsiu, “Fast acquisition and reconstruction of optical coherence tomography images via sparse representation,” IEEE Trans. Med. Imaging 32(11), 2034–2049 (2013).
[Crossref] [PubMed]

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

K. Li, X. Wu, D. Z. Chen, and M. Sonka, “Optimal surface segmentation in volumetric images--a graph-theoretic approach,” IEEE Trans. Pattern Anal. Mach. Intell. 28(1), 119–134 (2006).
[Crossref] [PubMed]

Invest. Ophthalmol. Vis. Sci. (12)

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]

H. Ishikawa, J. Kim, T. R. Friberg, G. Wollstein, L. Kagemann, M. L. Gabriele, K. A. Townsend, K. R. Sung, J. S. Duker, J. G. Fujimoto, and J. S. Schuman, “Three-dimensional optical coherence tomography (3D-OCT) image enhancement with segmentation-free contour modeling C-mode,” Invest. Ophthalmol. Vis. Sci. 50(3), 1344–1349 (2009).
[Crossref] [PubMed]

N. Jain, S. Farsiu, A. A. Khanifar, S. Bearelly, R. T. Smith, J. A. Izatt, and C. A. Toth, “Quantitative comparison of drusen segmented on SD-OCT versus drusen delineated on color fundus photographs,” Invest. Ophthalmol. Vis. Sci. 51(10), 4875–4883 (2010).
[Crossref] [PubMed]

L. de Sisternes, J. Hu, D. L. Rubin, and T. Leng, “Visual prognosis of eyes recovering from macular hole surgery through automated quantitative analysis of spectral-domain optical coherence tomography (SD-OCT) scans,” Invest. Ophthalmol. Vis. Sci. 56(8), 4631–4643 (2015).
[Crossref] [PubMed]

J. H. Acton, R. T. Smith, D. C. Hood, and V. C. Greenstein, “Relationship between retinal layer thickness and the visual field in early age-related macular degeneration,” Invest. Ophthalmol. Vis. Sci. 53(12), 7618–7624 (2012).
[Crossref] [PubMed]

J. R. Lee, J. W. Jeoung, J. Choi, J. Y. Choi, K. H. Park, and Y. D. Kim, “Structure-function relationships in normal and glaucomatous eyes determined by time- and spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6424–6430 (2010).
[Crossref] [PubMed]

L. de Sisternes, N. Simon, R. Tibshirani, T. Leng, and D. L. Rubin, “Quantitative SD-OCT imaging biomarkers as indicators of age-related macular degeneration progression,” Invest. Ophthalmol. Vis. Sci. 55(11), 7093–7103 (2014).
[Crossref] [PubMed]

F. G. Schlanitz, C. Ahlers, S. Sacu, C. Schütze, M. Rodriguez, S. Schriefl, I. Golbaz, T. Spalek, G. Stock, and U. Schmidt-Erfurth, “Performance of drusen detection by spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 51(12), 6715–6721 (2010).
[Crossref] [PubMed]

S. Y. Lee, P. F. Stetson, H. Ruiz-Garcia, F. M. Heussen, and S. R. Sadda, “Automated characterization of pigment epithelial detachment by optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53(1), 164–170 (2012).
[Crossref] [PubMed]

L. de Sisternes, J. Hu, D. L. Rubin, and M. F. Marmor, “Localization of damage in progressive hydroxychloroquine retinopathy on and off the drug: inner versus outer retina, parafovea versus peripheral fovea,” Invest. Ophthalmol. Vis. Sci. 56(5), 3415–3426 (2015).
[Crossref] [PubMed]

H. J. Lee, M. S. Kim, Y. J. Jo, and J. Y. Kim, “Thickness of the macula, retinal nerve fiber layer, and ganglion cell layer in the epiretinal membrane: The repeatability study of optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 56(8), 4554–4559 (2015).
[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]

J. R. Stat. Soc. Series C (1)

J. A. Hartigan and M. A. Wong, “Algorithm AS 136: A K-means clustering algorithm,” J. R. Stat. Soc. Series C 28(1), 100–108 (1979).

Med. Image Anal. (2)

R. Kafieh, H. Rabbani, M. D. Abramoff, and M. Sonka, “Intra-retinal layer segmentation of 3D optical coherence tomography using coarse grained diffusion map,” Med. Image Anal. 17(8), 907–928 (2013).
[Crossref] [PubMed]

Q. Chen, T. Leng, L. Zheng, L. Kutzscher, J. Ma, L. de Sisternes, and D. L. Rubin, “Automated drusen segmentation and quantification in SD-OCT images,” Med. Image Anal. 17(8), 1058–1072 (2013).
[Crossref] [PubMed]

Ophthalmology (2)

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, C. A. Toth, and Age-Related Eye Disease Study 2 Ancillary Spectral Domain Optical Coherence Tomography Study Group, “Quantitative classification of eyes with and without intermediate age-related macular degeneration using optical coherence tomography,” Ophthalmology 121(1), 162–172 (2014).
[Crossref] [PubMed]

G. Staurenghi, S. Sadda, U. Chakravarthy, R. F. Spaide, and International Nomenclature for Optical Coherence Tomography (IN•OCT) Panel, “Proposed lexicon for anatomic landmarks in normal posterior segment spectral-domain optical coherence tomography: the IN•OCT consensus,” Ophthalmology 121(8), 1572–1578 (2014).
[Crossref] [PubMed]

Opt. Express (4)

Science (1)

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Transl. Vis. Sci. Technol. (1)

A. Ehnes, Y. Wenner, C. Friedburg, M. N. Preising, W. Bowl, W. Sekundo, E. M. Zu Bexten, K. Stieger, and B. Lorenz, “Optical coherence tomography (OCT) device independent intraretinal layer segmentation,” Transl. Vis. Sci. Technol. 3(1), 1–16 (2014).
[Crossref] [PubMed]

Other (8)

S. Parrilli, M. Poderico, C. V. Angelino, G. Scarpa, and L. Verdoliva, “A non local approach for SAR image denoising,” IEEE Geoscience and Remote Sensing Symposium (IGARSS) (2010).

J. D’Errico, “Surface Fitting using gridfit” (MATLAB CENTRAL File Exchange, 12 Jul 2013, Updated 29 Jul 2010). http://www.mathworks.com/matlabcentral/fileexchange/8998-surface-fitting-using-gridfit .

S. J. Chiu, J. A. Izatt, R. V. O’Connell, K. P. Winter, C. A. Toth, and S. Farsiu, “Dataset for SD-OCT Retinal Image Analysis” (2012). http://people.duke.edu/~sf59/Chiu_IOVS_2011_dataset.htm .

Teng, and Pang-yu. “Caserel - An Open Source Software for Computer-aided Segmentation of Retinal Layers in Optical Coherence Tomography Images” (2013). http://pangyuteng.github.io/caserel/

M. Mayer, “Optical coherence tomography segmentation and evaluation GUI” (2016). https://www5.cs.fau.de/research/software/octseg/

P. A. Dufour, “OCT segmentation application” (2012). http://pascaldufour.net/Research/software_data.html

S. Farsiu, S. J. Chiu, R. V. O’Connell, F. A. Folgar, E. Yuan, J. A. Izatt, and C. A. Toth, “World’s largest annotated SD-OCT dataset for intermediate AMD and control subjects used in our recent paper” (accessed July 2013). http://people.duke.edu/~sf59/RPEDC_Ophth_2013_dataset.htm .

K. Lee, M. D. Abramoff, M. Garvin, and M. Sonka, “The Iowa Reference Algorithms. (Retinal Image Analysis Lab, Iowa Institute for Biomedical Imaging),” (accessed 12 Jan 2015, Updated 29 Sep 2014). https://www.iibi.uiowa.edu/content/iowa-reference-algorithms-human-and-murine-oct-retinal-layer-analysis-and-display

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Figures (13)

Fig. 1
Fig. 1 a) Example SD-OCT cube, comprising 3-D data. b) Example B-scan (planar images at each vertical location) within the cube, formed by a series of line-scans at each horizontal location (A-scans). c) Detail showing the location of each retinal boundary segmented by our proposed algorithm. The figure also indicates the correspondence between the nomenclature used in this work and the interface between two zones that each boundary represents, as defined in [39].
Fig. 2
Fig. 2 Steps in segmentation: Input data: SD-OCT cube. De-noising: (1) Non-local (NL) means filtering. Segmentation algorithm: (2) Initial ILM estimation, (3) ILM iterative segmentation, (4) differentiation of RNFL and RPE complexes, (5) initial estimation of remaining retinal layers, (6) iterative segmentation. Output: Segmented SD-OCT cube.
Fig. 3
Fig. 3 a) Rendering of the initial estimation of the 10 retinal boundaries. From top to bottom: Red: ILM. Green: i-RNFL. Dark blue: o-RNFL. Magenta: o-IPL. White: o-INL. Cyan: o-OPL. Green: i-EZ. Red: o-EZ. White: i-RPE. Yellow: o-RPE. b) Rendering of the retinal boundaries after refinement step. Axial differences between the layers are exaggerated for displaying purposes. c) On the left, example B-scan taken across the center of the fovea (top), and transverse scan across the center of the fovea (bottom). On the right, the same images are shown with the segmentation of the retinal boundaries after refinement step, as indicated by the legend displayed on the far right Note that the location of the segmented ILM boundary is not clearly visible in the B-scan and transverse scan since it has the same location as the i-RNFL boundary.
Fig. 4
Fig. 4 Example results in a sample SD-OCT B-scan from each group in Data set 1. The first, second and third rows show the results for a scan in group I (healthy), group II (early AMD), and group III (advanced AMD), respectively. First, second, third, fourth, and fifth columns: Original B-scan without outlines, with outlines resulting from our automated segmentation method, with outlines marked by the first and second reader, and with outlines resulting from the Iowa Reference Standard software, respectively (results for group III are not displayed since the Iowa software failed to produce any result). The labeling of each of the indicated boundaries is shown in in the legend in the top right.
Fig. 5
Fig. 5 Example results in an eye diagnosed with early AMD from Data set 2. First column: Original B-scan (top) and transverse scan (bottom) across the center of the fovea. Second column: Results produced by our automated method in the B-scan (top) and transverse scan (bottom). The labeling of the segmented boundaries is indicated by the legend in the right, from top to bottom. Note that the location of the ILM boundary (top red line) is not clearly visible because it has the same location as the i-RNFL boundary (top green line). Third column: Independent semi-automated outline locations of the ILM and i-RPE boundaries in the B-scan (top) and transverse scan (bottom).
Fig. 6
Fig. 6 Example results in an eye diagnosed with advanced AMD from Data set 2. First column: Original B-scan (top) and transverse scan (bottom) across the center of the fovea. The yellow circles in the bottom image indicate regions where substantial differences between the automated method and reference standard were observed. Second column: Results produced by our automated method in the B-scan (top) and transverse scan (bottom). The labeling of the segmented boundaries is indicated by the legend in the right, from top to bottom. Note that the location of the ILM boundary (top red line) is not clearly visible because it has the same location as the i-RNFL boundary (top green line). Third column: Independent semi-automated reference standard of the ILM and i-RPE boundaries in the B-scan (top) and transverse scan (bottom).
Fig. 7
Fig. 7 Results per group in quantitative comparisons among methods. Color codes are indicated in the legend and the error bars indicate standard deviation. Comparisons in group III of Data set 1 involving the Iowa Reference Standard software are missing since the software failed to produce any results. a) Comparison of axial MUE mean and std per group among the methods evaluated in Data set 1 (Cirrus scans). b) Axial MUE mean and std per group between our automated method and manually corrected reference standard in the Data set 2 (Bioptigen scans).
Fig. 8
Fig. 8 Comparison of visual accuracy between outlines determined by the first reader (dark blue), the second reader (cyan), our proposed automated method (yellow), and by the Iowa Reference Standard software (red). a) Mean visual accuracy scores per group and overall throughout groups. The error bars indicate standard deviation. b) Percentage of correct outlines, indicating no substantial editing (i.e. score of 1 or 2) needed according to the opinion of the third independent reader, per group and average across group.
Fig. 9
Fig. 9 a) Example of de-noised B-scan in cube. b) Axial gradient in the B-scan. c) Histogram from values in SD-OCT cube (blue line), estimated distribution of background values (red line) and selected threshold (green line). d) Segmented foreground region. e) Masked gradient. f) Histogram of values in foreground region.
Fig. 10
Fig. 10 a) Rendering of example ILM initial estimation. b), c), d) B-scans and ILM initial estimation corresponding to the red, green, and blue lines indicated in the rendering shown in a), respectively. e) Transverse scan (transverse cut of the SD-OCT cube in the axial-vertical plane) across the center of the fovea, corresponding to the yellow line in the rendering shown in a). f) Rendering of example with refined ILM. g), h), i) B-scans and refined ILM corresponding to the red, green, and blue lines indicated in the rendering shown in f), respectively. e) Transverse scan across the center of the fovea, corresponding to the yellow line in the rendering shown in f).
Fig. 11
Fig. 11 a) Example B-scan with voxels in the darker regions between the RNFL and RPE complexes identified in red. The blue line indicates the weighted mean axial position of these regions. b) Example B-scan with blue line indicating the separation of layers belonging to the RNFL and RPE complexes as identified in this work.
Fig. 12
Fig. 12 a) B-scan with initial estimation of retinal layer boundaries. From top to bottom: Red: ILM. Green: i-RNFL. Dark blue: o-RNFL. Magenta: o-IPL. White: o-INL. Cyan: o-OPL. Green: i-EZ. Red: o-EZ. White: i-RPE. Yellow: o-RPE. The red vertical line indicates a region of the A-scan for which the gradient profile is shown in (b). (c) Shows the filtered gradient profile with the initial identification of each boundary.
Fig. 13
Fig. 13 Example result in the estimation of the foveal pit location (indicated in red). a) Rendering of the segmented ILM layer, with foveal pit location. b) B-scan across the center of the fovea (location indicated by the blue line in a), with estimated foveal pit location indicated in red. b) Transverse scan across the center of the fovea (location indicated by the green line in a), with estimated foveal pit location indicated in red.

Tables (6)

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Table 1 Segmentation parameters chosen. Boundaries are indicated with the same acronyms as throughout the text. Coordinates (x,y) for each boundary are not indicated for simplicity.

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Table 2 Distribution of exams and outlines collected in the evaluation data sets. “Automated” refers to the method introduced here, “Iowa” refers to the Iowa Reference Algorithm software.

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Table 3 Meaning of accuracy rating scores assigned in qualitative evaluation, from 1 (most accurate) to 4 (failure to produce any result).

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Table 4 Pairwise segmentation differences in terms of mean unsigned axial positioning error for the methods evaluated in Data set 1. The mean and std (in parentheses) values are shown in microns. *Comparisons involving the Iowa Reference Standard software were limited to scans in groups I and II since the software failed to produce any results for scans in group III.

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Table 5 Segmentation differences in terms of axial MUE between our automated method and the independent semi-automated reference standard (Aut.-Reference Standard) in Data set 2. The mean and std (in parentheses) values are shown in microns.

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Table 6 Percentage of correct outlines (those receiving accuracy scores of 1 or 2 by an independent reader) from the first manual reader (R1) second manual reader (R2), our automated method (Aut.), and the Iowa Reference Standard software (Iowa) for each group and boundary. Values for the Iowa Reference Standard software in Group III are not shown since it failed to produce results in this group (all 0%).

Equations (5)

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B (x,y) k =           θ argmin n=L L m=L L W ( x,y, z k1 ( x,y;n,m;β ) ) k | z k1 ( x,y;n,m;β )θ |,
z k1 ( x,y;n,m;β )=B (x+n,y+m) k1 S ( x+n,y+m;β ) k1 +S ( x,y;β ) k1 .
W ( x,y,z ) k =r( α| I( x,y,z ) |sgn( I Z ( x,y,z ) ) )M ( x,y,z ) k ,
r( v )={ v, if v0 0, if v<0 ,
MUE( B 1 , B 2 )= x=1 I y=1 J | B 1 (x,y) B 2 (x,y) | IJ ,

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