Abstract

In age-related macular degeneration (AMD), the quantification of drusen is important because it is correlated with the evolution of the disease to an advanced stage. Therefore, we propose an algorithm based on a multi-surface framework for the segmentation of the limiting boundaries of drusen: the inner boundary of the retinal pigment epithelium + drusen complex (IRPEDC) and the Bruch’s membrane (BM). Several segmentation methods have been considerably successful in segmenting retinal layers of healthy retinas in optical coherence tomography (OCT) images. These methods are successful because they incorporate prior information and regularization. Nonetheless, these factors tend to hinder the segmentation for diseased retinas. The proposed algorithm takes into account the presence of drusen and geographic atrophy (GA) related to AMD by excluding prior information and regularization just valid for healthy regions. However, even with this algorithm, prior information and regularization still cause the oversmoothing of drusen in some locations. Thus, we propose the integration of local shape prior in the form of a sparse high order potentials (SHOPs) into the algorithm to reduce the oversmoothing of drusen. The proposed algorithm was evaluated in a public database. The mean unsigned errors, relative to the average of two experts, for the inner limiting membrane (ILM), IRPEDC and BM were 2.94±2.69, 5.53±5.66 and 4.00±4.00 µm, respectively. Drusen areas measurements were evaluated, relative to the average of two expert graders, by the mean absolute area difference and overlap ratio, which were 1579.7 ± 2106.8 µm2 and 0.78 ± 0.11, respectively.

© 2016 Optical Society of America

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References

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2016 (1)

F. A. Folgar, E. L. Yuan, M. B. Sevilla, S. J. Chiu, S. Farsiu, E. Y. Chew, and C. A. Toth, “Drusen Volume and Retinal Pigment Epithelium Abnormal Thinning Volume Predict 2-Year Progression of Age-Related Macular Degeneration,” Ophthalmology 123, 39–50 (2016).
[Crossref]

2014 (3)

G. Gregori, Z. Yehoshua, C. a. D. a. Garcia Filho, S. R. Sadda, R. Portella Nunes, W. J. Feuer, and P. J. Rosenfeld, “Change in drusen area over time compared using spectral-domain optical coherence tomography and color fundus imaging,” Invest. Ophthalmol. Vis. Sci. 55, 7662–7668 (2014).
[Crossref] [PubMed]

F. Shi, X. Chen, H. Zhao, W. Zhu, D. Xiang, E. Gao, M. Sonka, and H. Chen, “Automated 3-D Retinal Layer Segmentation of Macular Optical Coherence Tomography Images with Serous Pigment Epithelial Detachments,” IEEE Trans. Med. Imag. 34, 441–452 (2014).
[Crossref]

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

2013 (2)

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. Imag. 32, 531–543 (2013).
[Crossref]

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, 1058–1072 (2013).
[Crossref] [PubMed]

2012 (2)

D. Iwama, M. Hangai, S. Ooto, A. Sakamoto, H. Nakanishi, T. Fujimura, A. Domalpally, R. P. Danis, and N. Yoshimura, “Automated assessment of drusen using three-dimensional spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53, 1576–1583 (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. 5353 (2012).
[Crossref]

2010 (4)

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, 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, 6715–6721 (2010).
[Crossref] [PubMed]

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

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, 19413 (2010).
[Crossref] [PubMed]

2009 (3)

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. Imag. 28, 1436–1447 (2009).
[Crossref]

S. G. Schuman, A. F. Koreishi, S. Farsiu, S.-h. Jung, J. a. Izatt, and C. a. Toth, “Photoreceptor layer thinning over drusen in eyes with age-related macular degeneration imaged in vivo with spectral-domain optical coherence tomography,” Ophthalmology 116, 488–496 (2009).
[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, 176–181 (2009).
[Crossref]

2008 (1)

S. Farsiu, S. J. Chiu, J. a. Izatt, and C. a. Toth, “Fast Detection and Segmentation of Drusen in Retinal Optical Coherence Tomography Images,” Proc. SPIE 6844, 68440D12008).

2006 (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, 119–134 (2006).
[Crossref] [PubMed]

2003 (1)

P. T. Johnson, G. P. Lewis, K. C. Talaga, M. N. Brown, P. J. Kappel, S. K. Fisher, D. H. Anderson, and L. V. Johnson, “Drusen-Associated Degeneration in the Retina,” Invest. Ophthalmol. Vis. Sci. 44, 4481–4488 (2003).
[Crossref] [PubMed]

2001 (1)

K. B. Koozekanani and C. Roberts, “Retinal thickness measurements from optical coherence tomography using a Markov boundary model,” IEEE Trans. Medical Imag. 20, 900–9016 (2001).
[Crossref]

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. Imag. 32, 531–543 (2013).
[Crossref]

Abràmoff, M. D.

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. Imag. 28, 1436–1447 (2009).
[Crossref]

Adams, R. P.

J. M. Hernández-Lobato, M. A. Gelbart, M. W. Hoffman, R. P. Adams, and Z. Ghahramani, “Predictive Entropy Search for Bayesian Optimization with Unknown Constraints,” in “Proceedings of the 32nd Int. Conf. on Mach. Learning,” ( JMLR.org , 2015), pp. 1699–1707.

Ahlers, 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, 6715–6721 (2010).
[Crossref] [PubMed]

Anderson, D. H.

P. T. Johnson, G. P. Lewis, K. C. Talaga, M. N. Brown, P. J. Kappel, S. K. Fisher, D. H. Anderson, and L. V. Johnson, “Drusen-Associated Degeneration in the Retina,” Invest. Ophthalmol. Vis. Sci. 44, 4481–4488 (2003).
[Crossref] [PubMed]

Arshavsky, V. Y.

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, 4875–4883 (2010).
[Crossref] [PubMed]

Brown, M. N.

P. T. Johnson, G. P. Lewis, K. C. Talaga, M. N. Brown, P. J. Kappel, S. K. Fisher, D. H. Anderson, and L. V. Johnson, “Drusen-Associated Degeneration in the Retina,” Invest. Ophthalmol. Vis. Sci. 44, 4481–4488 (2003).
[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. Imag. 28, 1436–1447 (2009).
[Crossref]

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. Imag. 32, 531–543 (2013).
[Crossref]

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, 119–134 (2006).
[Crossref] [PubMed]

Chen, H.

F. Shi, X. Chen, H. Zhao, W. Zhu, D. Xiang, E. Gao, M. Sonka, and H. Chen, “Automated 3-D Retinal Layer Segmentation of Macular Optical Coherence Tomography Images with Serous Pigment Epithelial Detachments,” IEEE Trans. Med. Imag. 34, 441–452 (2014).
[Crossref]

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, 1058–1072 (2013).
[Crossref] [PubMed]

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, 176–181 (2009).
[Crossref]

Chen, X.

F. Shi, X. Chen, H. Zhao, W. Zhu, D. Xiang, E. Gao, M. Sonka, and H. Chen, “Automated 3-D Retinal Layer Segmentation of Macular Optical Coherence Tomography Images with Serous Pigment Epithelial Detachments,” IEEE Trans. Med. Imag. 34, 441–452 (2014).
[Crossref]

Chew, E. Y.

F. A. Folgar, E. L. Yuan, M. B. Sevilla, S. J. Chiu, S. Farsiu, E. Y. Chew, and C. A. Toth, “Drusen Volume and Retinal Pigment Epithelium Abnormal Thinning Volume Predict 2-Year Progression of Age-Related Macular Degeneration,” Ophthalmology 123, 39–50 (2016).
[Crossref]

Chiu, S. J.

F. A. Folgar, E. L. Yuan, M. B. Sevilla, S. J. Chiu, S. Farsiu, E. Y. Chew, and C. A. Toth, “Drusen Volume and Retinal Pigment Epithelium Abnormal Thinning Volume Predict 2-Year Progression of Age-Related Macular Degeneration,” Ophthalmology 123, 39–50 (2016).
[Crossref]

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. 5353 (2012).
[Crossref]

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, 19413 (2010).
[Crossref] [PubMed]

S. Farsiu, S. J. Chiu, J. a. Izatt, and C. a. Toth, “Fast Detection and Segmentation of Drusen in Retinal Optical Coherence Tomography Images,” Proc. SPIE 6844, 68440D12008).

Connell, R. V. O.

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. 5353 (2012).
[Crossref]

Danis, R. P.

D. Iwama, M. Hangai, S. Ooto, A. Sakamoto, H. Nakanishi, T. Fujimura, A. Domalpally, R. P. Danis, and N. Yoshimura, “Automated assessment of drusen using three-dimensional spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53, 1576–1583 (2012).
[Crossref] [PubMed]

de Boer, J. F.

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, 176–181 (2009).
[Crossref]

de Sisternes, 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, 1058–1072 (2013).
[Crossref] [PubMed]

Domalpally, A.

D. Iwama, M. Hangai, S. Ooto, A. Sakamoto, H. Nakanishi, T. Fujimura, A. Domalpally, R. P. Danis, and N. Yoshimura, “Automated assessment of drusen using three-dimensional spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53, 1576–1583 (2012).
[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. Imag. 32, 531–543 (2013).
[Crossref]

Dzanet, S. De

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. Imag. 32, 531–543 (2013).
[Crossref]

Farsiu, S.

F. A. Folgar, E. L. Yuan, M. B. Sevilla, S. J. Chiu, S. Farsiu, E. Y. Chew, and C. A. Toth, “Drusen Volume and Retinal Pigment Epithelium Abnormal Thinning Volume Predict 2-Year Progression of Age-Related Macular Degeneration,” Ophthalmology 123, 39–50 (2016).
[Crossref]

P. P. Srinivasan, S. J. Heflin, J. a. Izatt, V. Y. Arshavsky, and S. Farsiu, “Automatic segmentation of up to ten layer boundaries in SD-OCT images of the mouse retina with and without missing layers due to pathology,” Biomed. Opt. Express 5, 348 (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. 5353 (2012).
[Crossref]

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, 4875–4883 (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, 19413 (2010).
[Crossref] [PubMed]

S. G. Schuman, A. F. Koreishi, S. Farsiu, S.-h. Jung, J. a. Izatt, and C. a. Toth, “Photoreceptor layer thinning over drusen in eyes with age-related macular degeneration imaged in vivo with spectral-domain optical coherence tomography,” Ophthalmology 116, 488–496 (2009).
[Crossref] [PubMed]

S. Farsiu, S. J. Chiu, J. a. Izatt, and C. a. Toth, “Fast Detection and Segmentation of Drusen in Retinal Optical Coherence Tomography Images,” Proc. SPIE 6844, 68440D12008).

Feuer, W. J.

G. Gregori, Z. Yehoshua, C. a. D. a. Garcia Filho, S. R. Sadda, R. Portella Nunes, W. J. Feuer, and P. J. Rosenfeld, “Change in drusen area over time compared using spectral-domain optical coherence tomography and color fundus imaging,” Invest. Ophthalmol. Vis. Sci. 55, 7662–7668 (2014).
[Crossref] [PubMed]

Filho, C. a. D. a. Garcia

G. Gregori, Z. Yehoshua, C. a. D. a. Garcia Filho, S. R. Sadda, R. Portella Nunes, W. J. Feuer, and P. J. Rosenfeld, “Change in drusen area over time compared using spectral-domain optical coherence tomography and color fundus imaging,” Invest. Ophthalmol. Vis. Sci. 55, 7662–7668 (2014).
[Crossref] [PubMed]

Fisher, S. K.

P. T. Johnson, G. P. Lewis, K. C. Talaga, M. N. Brown, P. J. Kappel, S. K. Fisher, D. H. Anderson, and L. V. Johnson, “Drusen-Associated Degeneration in the Retina,” Invest. Ophthalmol. Vis. Sci. 44, 4481–4488 (2003).
[Crossref] [PubMed]

Folgar, F. A.

F. A. Folgar, E. L. Yuan, M. B. Sevilla, S. J. Chiu, S. Farsiu, E. Y. Chew, and C. A. Toth, “Drusen Volume and Retinal Pigment Epithelium Abnormal Thinning Volume Predict 2-Year Progression of Age-Related Macular Degeneration,” Ophthalmology 123, 39–50 (2016).
[Crossref]

Fujimura, T.

D. Iwama, M. Hangai, S. Ooto, A. Sakamoto, H. Nakanishi, T. Fujimura, A. Domalpally, R. P. Danis, and N. Yoshimura, “Automated assessment of drusen using three-dimensional spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53, 1576–1583 (2012).
[Crossref] [PubMed]

Gao, E.

F. Shi, X. Chen, H. Zhao, W. Zhu, D. Xiang, E. Gao, M. Sonka, and H. Chen, “Automated 3-D Retinal Layer Segmentation of Macular Optical Coherence Tomography Images with Serous Pigment Epithelial Detachments,” IEEE Trans. Med. Imag. 34, 441–452 (2014).
[Crossref]

Garvin, M. K.

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. Imag. 28, 1436–1447 (2009).
[Crossref]

Gelbart, M. A.

J. M. Hernández-Lobato, M. A. Gelbart, M. W. Hoffman, R. P. Adams, and Z. Ghahramani, “Predictive Entropy Search for Bayesian Optimization with Unknown Constraints,” in “Proceedings of the 32nd Int. Conf. on Mach. Learning,” ( JMLR.org , 2015), pp. 1699–1707.

Ghahramani, Z.

J. M. Hernández-Lobato, M. A. Gelbart, M. W. Hoffman, R. P. Adams, and Z. Ghahramani, “Predictive Entropy Search for Bayesian Optimization with Unknown Constraints,” in “Proceedings of the 32nd Int. Conf. on Mach. Learning,” ( JMLR.org , 2015), pp. 1699–1707.

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, 6715–6721 (2010).
[Crossref] [PubMed]

Gregori, G.

G. Gregori, Z. Yehoshua, C. a. D. a. Garcia Filho, S. R. Sadda, R. Portella Nunes, W. J. Feuer, and P. J. Rosenfeld, “Change in drusen area over time compared using spectral-domain optical coherence tomography and color fundus imaging,” Invest. Ophthalmol. Vis. Sci. 55, 7662–7668 (2014).
[Crossref] [PubMed]

Hangai, M.

D. Iwama, M. Hangai, S. Ooto, A. Sakamoto, H. Nakanishi, T. Fujimura, A. Domalpally, R. P. Danis, and N. Yoshimura, “Automated assessment of drusen using three-dimensional spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53, 1576–1583 (2012).
[Crossref] [PubMed]

Heflin, S. J.

Hernández-Lobato, J. M.

J. M. Hernández-Lobato, M. A. Gelbart, M. W. Hoffman, R. P. Adams, and Z. Ghahramani, “Predictive Entropy Search for Bayesian Optimization with Unknown Constraints,” in “Proceedings of the 32nd Int. Conf. on Mach. Learning,” ( JMLR.org , 2015), pp. 1699–1707.

Hoffman, M. W.

J. M. Hernández-Lobato, M. A. Gelbart, M. W. Hoffman, R. P. Adams, and Z. Ghahramani, “Predictive Entropy Search for Bayesian Optimization with Unknown Constraints,” in “Proceedings of the 32nd Int. Conf. on Mach. Learning,” ( JMLR.org , 2015), pp. 1699–1707.

Hornegger, J.

Iwama, D.

D. Iwama, M. Hangai, S. Ooto, A. Sakamoto, H. Nakanishi, T. Fujimura, A. Domalpally, R. P. Danis, and N. Yoshimura, “Automated assessment of drusen using three-dimensional spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53, 1576–1583 (2012).
[Crossref] [PubMed]

Izatt, J. a.

P. P. Srinivasan, S. J. Heflin, J. a. Izatt, V. Y. Arshavsky, and S. Farsiu, “Automatic segmentation of up to ten layer boundaries in SD-OCT images of the mouse retina with and without missing layers due to pathology,” Biomed. Opt. Express 5, 348 (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. 5353 (2012).
[Crossref]

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, 4875–4883 (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, 19413 (2010).
[Crossref] [PubMed]

S. G. Schuman, A. F. Koreishi, S. Farsiu, S.-h. Jung, J. a. Izatt, and C. a. Toth, “Photoreceptor layer thinning over drusen in eyes with age-related macular degeneration imaged in vivo with spectral-domain optical coherence tomography,” Ophthalmology 116, 488–496 (2009).
[Crossref] [PubMed]

S. Farsiu, S. J. Chiu, J. a. Izatt, and C. a. Toth, “Fast Detection and Segmentation of Drusen in Retinal Optical Coherence Tomography Images,” Proc. SPIE 6844, 68440D12008).

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, 4875–4883 (2010).
[Crossref] [PubMed]

Johnson, L. V.

P. T. Johnson, G. P. Lewis, K. C. Talaga, M. N. Brown, P. J. Kappel, S. K. Fisher, D. H. Anderson, and L. V. Johnson, “Drusen-Associated Degeneration in the Retina,” Invest. Ophthalmol. Vis. Sci. 44, 4481–4488 (2003).
[Crossref] [PubMed]

Johnson, P. T.

P. T. Johnson, G. P. Lewis, K. C. Talaga, M. N. Brown, P. J. Kappel, S. K. Fisher, D. H. Anderson, and L. V. Johnson, “Drusen-Associated Degeneration in the Retina,” Invest. Ophthalmol. Vis. Sci. 44, 4481–4488 (2003).
[Crossref] [PubMed]

Jung, S.-h.

S. G. Schuman, A. F. Koreishi, S. Farsiu, S.-h. Jung, J. a. Izatt, and C. a. Toth, “Photoreceptor layer thinning over drusen in eyes with age-related macular degeneration imaged in vivo with spectral-domain optical coherence tomography,” Ophthalmology 116, 488–496 (2009).
[Crossref] [PubMed]

Kappel, P. J.

P. T. Johnson, G. P. Lewis, K. C. Talaga, M. N. Brown, P. J. Kappel, S. K. Fisher, D. H. Anderson, and L. V. Johnson, “Drusen-Associated Degeneration in the Retina,” Invest. Ophthalmol. Vis. Sci. 44, 4481–4488 (2003).
[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, 4875–4883 (2010).
[Crossref] [PubMed]

Kohli, P.

C. Rother and P. Kohli, “Minimizing sparse higher order energy functions of discrete variables,” in “Proc. IEEE Conf. Computer Vision and Pattern Recognition,” (2009), pp. 1382–1389.

Kolmogorov, V.

C. Rother, V. Kolmogorov, V. Lempitsky, and M. Szummer, “Optimizing Binary MRFs via Extended Roof Duality,” Proc. IEEE Conf. Comput. Vis. Pattern Recognit. pp. 1–8 (2007).

Koozekanani, K. B.

K. B. Koozekanani and C. Roberts, “Retinal thickness measurements from optical coherence tomography using a Markov boundary model,” IEEE Trans. Medical Imag. 20, 900–9016 (2001).
[Crossref]

Koreishi, A. F.

S. G. Schuman, A. F. Koreishi, S. Farsiu, S.-h. Jung, J. a. Izatt, and C. a. Toth, “Photoreceptor layer thinning over drusen in eyes with age-related macular degeneration imaged in vivo with spectral-domain optical coherence tomography,” Ophthalmology 116, 488–496 (2009).
[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. Imag. 32, 531–543 (2013).
[Crossref]

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, 1058–1072 (2013).
[Crossref] [PubMed]

Lempitsky, V.

C. Rother, V. Kolmogorov, V. Lempitsky, and M. Szummer, “Optimizing Binary MRFs via Extended Roof Duality,” Proc. IEEE Conf. Comput. Vis. Pattern Recognit. pp. 1–8 (2007).

Leng, T.

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, 1058–1072 (2013).
[Crossref] [PubMed]

Lewis, G. P.

P. T. Johnson, G. P. Lewis, K. C. Talaga, M. N. Brown, P. J. Kappel, S. K. Fisher, D. H. Anderson, and L. V. Johnson, “Drusen-Associated Degeneration in the Retina,” Invest. Ophthalmol. Vis. Sci. 44, 4481–4488 (2003).
[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, 119–134 (2006).
[Crossref] [PubMed]

Li, X. T.

Liu, Y.

Q. Song, X. Wu, and Y. Liu, “Simultaneous searching of globally optimal interacting surfaces with shape priors,” in “IEEE Conf. Comput. Vis. Pattern Recognit.” pp. 2879–2886 (2010).

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, 1058–1072 (2013).
[Crossref] [PubMed]

Mardin, C.

Mayer, M.

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, 176–181 (2009).
[Crossref]

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, 176–181 (2009).
[Crossref]

Nakanishi, H.

D. Iwama, M. Hangai, S. Ooto, A. Sakamoto, H. Nakanishi, T. Fujimura, A. Domalpally, R. P. Danis, and N. Yoshimura, “Automated assessment of drusen using three-dimensional spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53, 1576–1583 (2012).
[Crossref] [PubMed]

Nicholas, P.

Nunes, R. Portella

G. Gregori, Z. Yehoshua, C. a. D. a. Garcia Filho, S. R. Sadda, R. Portella Nunes, W. J. Feuer, and P. J. Rosenfeld, “Change in drusen area over time compared using spectral-domain optical coherence tomography and color fundus imaging,” Invest. Ophthalmol. Vis. Sci. 55, 7662–7668 (2014).
[Crossref] [PubMed]

Ooto, S.

D. Iwama, M. Hangai, S. Ooto, A. Sakamoto, H. Nakanishi, T. Fujimura, A. Domalpally, R. P. Danis, and N. Yoshimura, “Automated assessment of drusen using three-dimensional spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53, 1576–1583 (2012).
[Crossref] [PubMed]

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, 176–181 (2009).
[Crossref]

Roberts, C.

K. B. Koozekanani and C. Roberts, “Retinal thickness measurements from optical coherence tomography using a Markov boundary model,” IEEE Trans. Medical Imag. 20, 900–9016 (2001).
[Crossref]

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, 6715–6721 (2010).
[Crossref] [PubMed]

Rosenfeld, P. J.

G. Gregori, Z. Yehoshua, C. a. D. a. Garcia Filho, S. R. Sadda, R. Portella Nunes, W. J. Feuer, and P. J. Rosenfeld, “Change in drusen area over time compared using spectral-domain optical coherence tomography and color fundus imaging,” Invest. Ophthalmol. Vis. Sci. 55, 7662–7668 (2014).
[Crossref] [PubMed]

Rother, C.

C. Rother and P. Kohli, “Minimizing sparse higher order energy functions of discrete variables,” in “Proc. IEEE Conf. Computer Vision and Pattern Recognition,” (2009), pp. 1382–1389.

C. Rother, V. Kolmogorov, V. Lempitsky, and M. Szummer, “Optimizing Binary MRFs via Extended Roof Duality,” Proc. IEEE Conf. Comput. Vis. Pattern Recognit. pp. 1–8 (2007).

Rubin, D. 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, 1058–1072 (2013).
[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. Imag. 28, 1436–1447 (2009).
[Crossref]

Sacu, 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, 6715–6721 (2010).
[Crossref] [PubMed]

Sadda, S. R.

G. Gregori, Z. Yehoshua, C. a. D. a. Garcia Filho, S. R. Sadda, R. Portella Nunes, W. J. Feuer, and P. J. Rosenfeld, “Change in drusen area over time compared using spectral-domain optical coherence tomography and color fundus imaging,” Invest. Ophthalmol. Vis. Sci. 55, 7662–7668 (2014).
[Crossref] [PubMed]

Sakamoto, A.

D. Iwama, M. Hangai, S. Ooto, A. Sakamoto, H. Nakanishi, T. Fujimura, A. Domalpally, R. P. Danis, and N. Yoshimura, “Automated assessment of drusen using three-dimensional spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53, 1576–1583 (2012).
[Crossref] [PubMed]

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, 6715–6721 (2010).
[Crossref] [PubMed]

Schmidt-Erfurth, U.

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, 6715–6721 (2010).
[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, 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. Imag. 32, 531–543 (2013).
[Crossref]

Schuman, S. G.

S. G. Schuman, A. F. Koreishi, S. Farsiu, S.-h. Jung, J. a. Izatt, and C. a. Toth, “Photoreceptor layer thinning over drusen in eyes with age-related macular degeneration imaged in vivo with spectral-domain optical coherence tomography,” Ophthalmology 116, 488–496 (2009).
[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, 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, 176–181 (2009).
[Crossref]

Sevilla, M. B.

F. A. Folgar, E. L. Yuan, M. B. Sevilla, S. J. Chiu, S. Farsiu, E. Y. Chew, and C. A. Toth, “Drusen Volume and Retinal Pigment Epithelium Abnormal Thinning Volume Predict 2-Year Progression of Age-Related Macular Degeneration,” Ophthalmology 123, 39–50 (2016).
[Crossref]

Shi, F.

F. Shi, X. Chen, H. Zhao, W. Zhu, D. Xiang, E. Gao, M. Sonka, and H. Chen, “Automated 3-D Retinal Layer Segmentation of Macular Optical Coherence Tomography Images with Serous Pigment Epithelial Detachments,” IEEE Trans. Med. Imag. 34, 441–452 (2014).
[Crossref]

Smith, R. T.

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, 4875–4883 (2010).
[Crossref] [PubMed]

Song, Q.

Q. Song, X. Wu, and Y. Liu, “Simultaneous searching of globally optimal interacting surfaces with shape priors,” in “IEEE Conf. Comput. Vis. Pattern Recognit.” pp. 2879–2886 (2010).

Sonka, M.

F. Shi, X. Chen, H. Zhao, W. Zhu, D. Xiang, E. Gao, M. Sonka, and H. Chen, “Automated 3-D Retinal Layer Segmentation of Macular Optical Coherence Tomography Images with Serous Pigment Epithelial Detachments,” IEEE Trans. Med. Imag. 34, 441–452 (2014).
[Crossref]

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. Imag. 28, 1436–1447 (2009).
[Crossref]

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, 119–134 (2006).
[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, 6715–6721 (2010).
[Crossref] [PubMed]

Srinivasan, P. P.

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, 6715–6721 (2010).
[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, 176–181 (2009).
[Crossref]

Szummer, M.

C. Rother, V. Kolmogorov, V. Lempitsky, and M. Szummer, “Optimizing Binary MRFs via Extended Roof Duality,” Proc. IEEE Conf. Comput. Vis. Pattern Recognit. pp. 1–8 (2007).

Talaga, K. C.

P. T. Johnson, G. P. Lewis, K. C. Talaga, M. N. Brown, P. J. Kappel, S. K. Fisher, D. H. Anderson, and L. V. Johnson, “Drusen-Associated Degeneration in the Retina,” Invest. Ophthalmol. Vis. Sci. 44, 4481–4488 (2003).
[Crossref] [PubMed]

Tornow, R.

Toth, C. A.

F. A. Folgar, E. L. Yuan, M. B. Sevilla, S. J. Chiu, S. Farsiu, E. Y. Chew, and C. A. Toth, “Drusen Volume and Retinal Pigment Epithelium Abnormal Thinning Volume Predict 2-Year Progression of Age-Related Macular Degeneration,” Ophthalmology 123, 39–50 (2016).
[Crossref]

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. 5353 (2012).
[Crossref]

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, 4875–4883 (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, 19413 (2010).
[Crossref] [PubMed]

S. G. Schuman, A. F. Koreishi, S. Farsiu, S.-h. Jung, J. a. Izatt, and C. a. Toth, “Photoreceptor layer thinning over drusen in eyes with age-related macular degeneration imaged in vivo with spectral-domain optical coherence tomography,” Ophthalmology 116, 488–496 (2009).
[Crossref] [PubMed]

S. Farsiu, S. J. Chiu, J. a. Izatt, and C. a. Toth, “Fast Detection and Segmentation of Drusen in Retinal Optical Coherence Tomography Images,” Proc. SPIE 6844, 68440D12008).

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. 5353 (2012).
[Crossref]

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. Imag. 32, 531–543 (2013).
[Crossref]

Wood, A.

A. Wood, “Retinal structure and function in age-related maculopathy,” Ph.D. thesis, Cardiff University (2011).

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. Imag. 28, 1436–1447 (2009).
[Crossref]

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, 119–134 (2006).
[Crossref] [PubMed]

Q. Song, X. Wu, and Y. Liu, “Simultaneous searching of globally optimal interacting surfaces with shape priors,” in “IEEE Conf. Comput. Vis. Pattern Recognit.” pp. 2879–2886 (2010).

Xiang, D.

F. Shi, X. Chen, H. Zhao, W. Zhu, D. Xiang, E. Gao, M. Sonka, and H. Chen, “Automated 3-D Retinal Layer Segmentation of Macular Optical Coherence Tomography Images with Serous Pigment Epithelial Detachments,” IEEE Trans. Med. Imag. 34, 441–452 (2014).
[Crossref]

Yehoshua, Z.

G. Gregori, Z. Yehoshua, C. a. D. a. Garcia Filho, S. R. Sadda, R. Portella Nunes, W. J. Feuer, and P. J. Rosenfeld, “Change in drusen area over time compared using spectral-domain optical coherence tomography and color fundus imaging,” Invest. Ophthalmol. Vis. Sci. 55, 7662–7668 (2014).
[Crossref] [PubMed]

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, 176–181 (2009).
[Crossref]

Yoshimura, N.

D. Iwama, M. Hangai, S. Ooto, A. Sakamoto, H. Nakanishi, T. Fujimura, A. Domalpally, R. P. Danis, and N. Yoshimura, “Automated assessment of drusen using three-dimensional spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53, 1576–1583 (2012).
[Crossref] [PubMed]

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, 176–181 (2009).
[Crossref]

Yuan, E. L.

F. A. Folgar, E. L. Yuan, M. B. Sevilla, S. J. Chiu, S. Farsiu, E. Y. Chew, and C. A. Toth, “Drusen Volume and Retinal Pigment Epithelium Abnormal Thinning Volume Predict 2-Year Progression of Age-Related Macular Degeneration,” Ophthalmology 123, 39–50 (2016).
[Crossref]

Zhao, H.

F. Shi, X. Chen, H. Zhao, W. Zhu, D. Xiang, E. Gao, M. Sonka, and H. Chen, “Automated 3-D Retinal Layer Segmentation of Macular Optical Coherence Tomography Images with Serous Pigment Epithelial Detachments,” IEEE Trans. Med. Imag. 34, 441–452 (2014).
[Crossref]

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, 1058–1072 (2013).
[Crossref] [PubMed]

Zhu, W.

F. Shi, X. Chen, H. Zhao, W. Zhu, D. Xiang, E. Gao, M. Sonka, and H. Chen, “Automated 3-D Retinal Layer Segmentation of Macular Optical Coherence Tomography Images with Serous Pigment Epithelial Detachments,” IEEE Trans. Med. Imag. 34, 441–452 (2014).
[Crossref]

Biomed. Opt. Express (2)

Br. J. Ophthalmol. (1)

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, 176–181 (2009).
[Crossref]

IEEE Trans. Med. Imag. (3)

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. Imag. 28, 1436–1447 (2009).
[Crossref]

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. Imag. 32, 531–543 (2013).
[Crossref]

F. Shi, X. Chen, H. Zhao, W. Zhu, D. Xiang, E. Gao, M. Sonka, and H. Chen, “Automated 3-D Retinal Layer Segmentation of Macular Optical Coherence Tomography Images with Serous Pigment Epithelial Detachments,” IEEE Trans. Med. Imag. 34, 441–452 (2014).
[Crossref]

IEEE Trans. Medical Imag. (1)

K. B. Koozekanani and C. Roberts, “Retinal thickness measurements from optical coherence tomography using a Markov boundary model,” IEEE Trans. Medical Imag. 20, 900–9016 (2001).
[Crossref]

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, 119–134 (2006).
[Crossref] [PubMed]

Invest. Ophthalmol. Vis. Sci. (6)

G. Gregori, Z. Yehoshua, C. a. D. a. Garcia Filho, S. R. Sadda, R. Portella Nunes, W. J. Feuer, and P. J. Rosenfeld, “Change in drusen area over time compared using spectral-domain optical coherence tomography and color fundus imaging,” Invest. Ophthalmol. Vis. Sci. 55, 7662–7668 (2014).
[Crossref] [PubMed]

P. T. Johnson, G. P. Lewis, K. C. Talaga, M. N. Brown, P. J. Kappel, S. K. Fisher, D. H. Anderson, and L. V. Johnson, “Drusen-Associated Degeneration in the Retina,” Invest. Ophthalmol. Vis. Sci. 44, 4481–4488 (2003).
[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. 5353 (2012).
[Crossref]

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, 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, 6715–6721 (2010).
[Crossref] [PubMed]

D. Iwama, M. Hangai, S. Ooto, A. Sakamoto, H. Nakanishi, T. Fujimura, A. Domalpally, R. P. Danis, and N. Yoshimura, “Automated assessment of drusen using three-dimensional spectral-domain optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 53, 1576–1583 (2012).
[Crossref] [PubMed]

Med. Image Anal. (1)

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, 1058–1072 (2013).
[Crossref] [PubMed]

Ophthalmology (2)

S. G. Schuman, A. F. Koreishi, S. Farsiu, S.-h. Jung, J. a. Izatt, and C. a. Toth, “Photoreceptor layer thinning over drusen in eyes with age-related macular degeneration imaged in vivo with spectral-domain optical coherence tomography,” Ophthalmology 116, 488–496 (2009).
[Crossref] [PubMed]

F. A. Folgar, E. L. Yuan, M. B. Sevilla, S. J. Chiu, S. Farsiu, E. Y. Chew, and C. A. Toth, “Drusen Volume and Retinal Pigment Epithelium Abnormal Thinning Volume Predict 2-Year Progression of Age-Related Macular Degeneration,” Ophthalmology 123, 39–50 (2016).
[Crossref]

Opt. Express (1)

Proc. SPIE (1)

S. Farsiu, S. J. Chiu, J. a. Izatt, and C. a. Toth, “Fast Detection and Segmentation of Drusen in Retinal Optical Coherence Tomography Images,” Proc. SPIE 6844, 68440D12008).

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Acess Economics Pty Limited, “The Global Economic Cost of Visual Impairment,” Tech. Rep. March (2010).

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C. Rother and P. Kohli, “Minimizing sparse higher order energy functions of discrete variables,” in “Proc. IEEE Conf. Computer Vision and Pattern Recognition,” (2009), pp. 1382–1389.

Q. Song, X. Wu, and Y. Liu, “Simultaneous searching of globally optimal interacting surfaces with shape priors,” in “IEEE Conf. Comput. Vis. Pattern Recognit.” pp. 2879–2886 (2010).

J. M. Hernández-Lobato, M. A. Gelbart, M. W. Hoffman, R. P. Adams, and Z. Ghahramani, “Predictive Entropy Search for Bayesian Optimization with Unknown Constraints,” in “Proceedings of the 32nd Int. Conf. on Mach. Learning,” ( JMLR.org , 2015), pp. 1699–1707.

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Figures (7)

Fig. 1
Fig. 1 Automatic segmentation with the proposed method of an OCT frame in the fovea region with the presence large drusen. IS-OS represents the boundary between the inner segment (IS) and the outer segment (OS) of the photoreceptor layer, while retina layer refers to the neurosensory retina, which excludes the RPEDC.
Fig. 2
Fig. 2 Representation of the surface Si as a height function fi(x,y) = x in graph Vi. Nodes in red represent the closed set and its top nodes of each (x,y) column represent surface Si. The nodes of each (x,y) column are connected by a gray line. The grid structure corresponds to the volumetric image I.
Fig. 3
Fig. 3 Example of a SHOP with compact representation. Labeling L is presented in (a). The Hamming distances (HD) relative to (a) and costs of segmentations (b), (c) and (d) consider that p = 5, leading to θ = 45.
Fig. 4
Fig. 4 Segmentation of IRPEDC (green) without SHOPs [(a), (c)] and with SHOPs [(b, d)]. The SHOPs are presented in (a) and (c); the red and purple pixels represent labels 0 and 1 of the SHOPs, respectively. Boundaries ILM (orange), IS-OS (blue) and BM (yellow) are presented in (b) and (d).
Fig. 5
Fig. 5 Detection and application of SHOPs. The original image is presented in (a). In (b), IRPEDC from subsection 2.2.6 is in green, while IRPEDC without soft constraints from subsection 2.2.7 is in red. Image (c) refers to the difference between these two segmentations, which is used to define the cliques for each SHOP (rectangles in cyan). Image (d) shows the IRPEDC segmentation using SHOPs (subsection 2.2.8) after the post-processing in green and the favored labelings (LIRPEDC) in red and purple for the labels 0 and 1, respectively.
Fig. 6
Fig. 6 Results of the proposed method without SHOPs [(a),(c)] and Dufour’s method for healthy retinas [(b),(d)]. Images (a) and (b) refer to a case of large drusen, while (c) and (d) to a GA region. Depicted boundaries are: ILM (orange), IS-OS (blue), IRPEDC (green) and BM (yellow).
Fig. 7
Fig. 7 Detection and application of SHOPs in a case where SHOPs are incorrectly defined. The original image is presented in (a). In (b), IRPEDC from subsection 2.2.6 is in green, while IRPEDC without soft constraints from subsection 2.2.7 is in red. Image (c) refers to the difference between these two segmentations, which is used to define the cliques for each SHOP (rectangles in cyan). Image (d) shows the IRPEDC segmentation using SHOPs (subsection 2.2.8) after the post-processing in green and the favored labelings (LIRPEDC) in red and purple for the labels 0 and 1, respectively.

Tables (4)

Tables Icon

Table 1 Overall mean unsigned error (± standard deviation) in µm. The lowest values of mean and standard deviation for each expert are shown in bold. Statistically significant results greater or lower than those of the proposed method are indicated by ↑ and ↓, respectively. The absence of symbols signifies no statistical difference between results. Statistical significance was determined by p-values < 0.05 computed with a two-sided Wilcoxon signed-ranked test (for paired data).

Tables Icon

Table 2 Mean unsigned error (± standard deviation) in µm of drusen regions and non-drusen regions. The lowest values of mean and standard deviation for each expert are shown in bold. Statistically significant results greater or lower than those of the proposed method are indicated by ↑ and ↓, respectively. The absence of symbols signifies no statistical difference between results. Statistical significance was determined by p-values < 0.05 computed with a two-sided Wilcoxon signed-ranked test (for paired data). G refers to the expert grader.

Tables Icon

Table 3 Average absolute area difference in µm2 and overlap ratio of drusen areas. The best values of mean and standard deviation for each expert are shown in bold. Statistically significant results greater or lower than those of the proposed method are indicated by and ↓, respectively. The absence of symbols signifies no statistical difference between results. Statistical significance was determined by p-values < 0.05 computed with a two-sided Wilcoxon signed-ranked test (for paired data).

Tables Icon

Table 4 Mean signed error (± standard deviation) in µm without any offset correction.

Equations (13)

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E ( S ) = i = 1 n ( E b o u n d ( S i ) + E s m o o t h ( S i ) ) + i = 1 n 1 j = i + 1 n E i n t e r ( S i , S j ) + i = 1 n L L i E S H O P ( S i , L ) ,
Δ x m a x ( x , y ) = Δ x h μ i ( x , y ) + β Δ x h σ i ( x , y ) ,
Δ x m i n ( x , y ) = Δ x h μ i ( x , y ) β Δ x h σ i ( x , y ) ,
E s m o o t h ( S i ) = x X , y Y ( λ i x | Δ f i ( x , y ) Δ x Δ x h μ i ( x , y ) | ) ,
δ u i , j ( x , y ) = d μ i , j ( x , y ) β d σ i , j ( x , y ) ,
δ l i , j ( x , y ) = d μ i , j ( x , y ) + β d σ i , j ( x , y ) ,
E i n t e r ( S i , S j ) = x X , y Y α i j d σ i , j ( x , y ) | d i , j ( x , y ) d μ i , j ( x , y ) | ,
ψ c ( l c , L ) = { θ 0 , if l c = L θ m a x , o t h e r w i s e , or ψ c ( l c , L ) = { 0 , if l c = L θ , o t h e r w i s e ,
g ( l c , L ) = θ v c | w v | 1 l c ( v ) L ( v ) ,
ψ c g ( l c , L ) = m i n { g ( l c , L ) , θ } ,
θ = p | c | , w v = { 1 / | c | , if L ( v ) = 0 1 / | c | , if L ( v ) = 1 .
ψ c g ( l c , L ) = v c p 1 l c ( v ) L ( v ) ,
E S H O P ( S , L ) = ψ c g ( l c , L ) , if l c = Ω ( S ) ,

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