Abstract

In this paper we present a novel method for the segmentation of thin corrugated layers in high resolution optical coherence tomography (OCT) images. First, we make an initial segmentation, for example with graph based segmentation that, for highly corrugated interfaces, leads to many segmentation errors. Second, we resegment the initial outcome, based on the OCT attenuation coefficient image with our matching layer attenuation coefficient segmentation (MLAS) algorithm. This algorithm repositions the initial segmentation such that it finds the point where the attenuation coefficient is close to the mean centerline attenuation. The algorithm does not utilize any sample specific prior knowledge in the attenuation coefficient based segmentation step. For simulated and measured data of strongly corrugated samples, such as is the case for varnish layers on paintings and furniture, the MLAS algorithm performs much better than the conventional segmentation. Finally, we show 3D segmentation of an entire 190 mm3 OCT volume. Our technique can aid in the rapid characterization of layer stratigraphy and deepen our understanding of their condition.

© 2017 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Full Article  |  PDF Article
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  1. Y. Dong, S. Lawman, Y. Zheng, D. Williams, J. Zhang, and Y.-C. Shen, “Nondestructive analysis of automotive paints with spectral domain optical coherence tomography,” Appl. Opt. 55, 3695–3700 (2016).
    [Crossref] [PubMed]
  2. Y. Dong, H. Lin, V. Abolghasemi, L. Gan, J. A. Zeitler, and Y.-C. Shen, “Investigating intra-tablet coating uniformity with spectral-domain optical coherence tomography,” J. Pharm. Sci. 106, 546–553 (2017).
    [Crossref]
  3. G. Fresquet and J.-P. Piel, “Optical characterization and defect inspection for 3D stacked IC technology,” International Symposium on Microelectronics 2014, 000630 (2014).
    [Crossref]
  4. S.-H. Kim, J.-H. Kim, and S.-W. Kang, “Nondestructive defect inspection for LCDs using optical coherence tomography,” Displays 32, 325–329 (2011).
    [Crossref]
  5. M. R. Hee, C. R. Baumal, C. A. Puliafito, J. S. Duker, E. Reichel, J. R. Wilkins, J. G. Coker, J. S. Schuman, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography of age-related macular degeneration and choroidal neovascularization,” Ophthalmology 103, 1260–1270 (1996).
    [Crossref] [PubMed]
  6. T. R. G. Babu, S. S. Devi, and R. Venkatesh, “Automatic detection of glaucoma using optical coherence tomography image,” J. Appl. Sci. 12, 2128–2138 (2012).
    [Crossref]
  7. M.-L. Yang, C.-W. Lu, I.-J. Hsu, and C. C. Yang, “The use of optical coherence tomography for monitoring the subsurface morphologies of archaic jades,” Archaeometry 46, 171–182 (2004).
    [Crossref]
  8. P. Targowski, B. Rouba, M. Góra, L. Tyminska-Widmer, J. Marczak, and A. Kowalczyk, “Optical coherence tomography in art diagnostics and restoration,” Appl. Phys. A 92, 1–9 (2008).
    [Crossref]
  9. M. Lenz, C. Mazzon, C. Dillmann, N. C. Gerhardt, H. Welp, M. Prange, and M. R. Hofmann, “Spectral domain optical coherence tomography for non-destructive testing of protection coatings on metal substrates,” Appl. Sci. 7364 (2017).
    [Crossref]
  10. J. Striova, B. Salvadori, R. Fontana, A. Sansonetti, M. Barucci, E. Pampaloni, E. Marconi, L. Pezzati, and M. P. Colombini, “Optical and spectroscopic tools for evaluating Er:YAG laser removal of shellac varnish,” Stud. Conserv. 60, S91–S96 (2015).
    [Crossref]
  11. S. Lawman and H. Liang, “High precision dynamic multi-interface profilometry with optical coherence tomography,” Appl. Opt. 50, 6039–6048 (2011).
    [Crossref] [PubMed]
  12. G. Michalina, P. Targowski, A. Rycyk, and J. Marczak, “Varnish ablation control by optical coherence tomography,” Laser Chem. 2006, 10647 (2007).
  13. J. K. Delaney, E. R. de la Rie, M. Elias, L.-P. Sung, and K. M. Morales, “The role of varnishes in modifying light reflection from rough surfaces - a study of changes in light scattering caused by variations in varnish topography and development of a drying model,” Stud. Conserv. 53, 170–186 (2008).
    [Crossref]
  14. E. R. de la Rie, “The influence of varnishes on the appearance of paintings,” Stud. Conserv. 32, 1–13 (1987).
  15. J. J. Hermans, K. Keune, A. van Loon, and P. D. Iedema, “An infrared spectroscopic study of the nature of zinc carboxylates in oil paintings,” J. Anal. At. Spectrom. 30, 1600–1608 (2015).
    [Crossref]
  16. D. Ciofini, M. Oujja, M. V. Canamares, S. Siano, and M. Castillejo, “Spectroscopic assessment of the UV laser removal of varnishes from painted surfaces,” Microchem. J. 124, 792–803 (2015).
    [Crossref]
  17. P. Pouli, I.-A. Paun, G. Bounos, S. Georgiou, and C. Fotakis, “The potential of UV femtosecond laser ablation for varnish removal in the restoration of painted works of art,” Applied Surface Science 254, 6875–6879 (2008).
    [Crossref]
  18. C. S. Cheung, M. Spring, and H. Liang, “Ultra-high resolution Fourier domain optical coherence tomography for old master paintings,” Opt. Express 23, 10145–10157 (2015).
    [Crossref] [PubMed]
  19. J. Novosel, G. Thepass, H. G. Lemij, J. F. de Boer, K. A. Vermeer, and L. J. van Vliet, “Loosely coupled level sets for simultaneous 3D retinal layer segmentation in optical coherence tomography,” Med. Image Anal. 26, 146–158 (2015).
    [Crossref] [PubMed]
  20. F. van der Lijn, T. den Heijer, M. M. Breteler, and W. J. Niessen, “Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts,” NeuroImage 43, 708–720 (2008).
    [Crossref] [PubMed]
  21. 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, 19413–19428 (2010).
    [Crossref] [PubMed]
  22. L. Zhang, H. Kong, S. Liu, T. Wang, S. Chen, and M. Sonka, “Graph-based segmentation of abnormal nuclei in cervical cytology,” Comput. Med. Imaging Graphics 56, 38–48 (2017).
    [Crossref]
  23. D. Williams, Y. Zheng, F. Bao, and A. Elsheikh, “Fast segmentation of anterior segment optical coherence tomography images using graph cut,” Eye and Vision 2, 1 (2015).
    [Crossref] [PubMed]
  24. D. Kaba, Y. Wang, C. Wang, X. Liu, H. Zhu, A. G. Salazar-Gonzalez, and Y. Li, “Retina layer segmentation using kernel graph cuts and continuous max-flow,” Opt. Express 23, 7366–7384 (2015).
    [Crossref] [PubMed]
  25. K. A. Vermeer, J. Mo, J. J. A. Weda, H. G. Lemij, and J. F. de Boer, “Depth-resolved model-based reconstruction of attenuation coefficients in optical coherence tomography,” Biomed. Opt. Express 5, 322–337 (2014).
    [Crossref] [PubMed]
  26. D. Hillmann, “Holoscopy,” Springer (2014).
  27. N. A. Nassif, B. Cense, B. H. Park, M. C. Pierce, S. H. Yun, B. E. Bouma, G. J. Tearney, T. C. Chen, and J. F. de Boer, “In vivo high-resolution video-rate spectral-domain optical coherence tomography of the human retina and optic nerve,” Opt. Express 12, 367–376 (2004).
    [Crossref] [PubMed]
  28. J. Kalkman, “Fourier-domain optical coherence tomography signal analysis and numerical modeling,” Int. J. Opt. 229586067 (2017).
  29. E. Dijkstra, “A note on two problems in connexion with graphs,” Numer. Math 1, 269–271 (1959).
    [Crossref]
  30. J. Shi and J. Malik, “Normalized cuts and image segmentation,” IEEE Trans. Pattern Anal. Mach. Intell. 22, 888–905 (2000).
    [Crossref]

2017 (4)

Y. Dong, H. Lin, V. Abolghasemi, L. Gan, J. A. Zeitler, and Y.-C. Shen, “Investigating intra-tablet coating uniformity with spectral-domain optical coherence tomography,” J. Pharm. Sci. 106, 546–553 (2017).
[Crossref]

M. Lenz, C. Mazzon, C. Dillmann, N. C. Gerhardt, H. Welp, M. Prange, and M. R. Hofmann, “Spectral domain optical coherence tomography for non-destructive testing of protection coatings on metal substrates,” Appl. Sci. 7364 (2017).
[Crossref]

L. Zhang, H. Kong, S. Liu, T. Wang, S. Chen, and M. Sonka, “Graph-based segmentation of abnormal nuclei in cervical cytology,” Comput. Med. Imaging Graphics 56, 38–48 (2017).
[Crossref]

J. Kalkman, “Fourier-domain optical coherence tomography signal analysis and numerical modeling,” Int. J. Opt. 229586067 (2017).

2016 (1)

2015 (7)

D. Kaba, Y. Wang, C. Wang, X. Liu, H. Zhu, A. G. Salazar-Gonzalez, and Y. Li, “Retina layer segmentation using kernel graph cuts and continuous max-flow,” Opt. Express 23, 7366–7384 (2015).
[Crossref] [PubMed]

C. S. Cheung, M. Spring, and H. Liang, “Ultra-high resolution Fourier domain optical coherence tomography for old master paintings,” Opt. Express 23, 10145–10157 (2015).
[Crossref] [PubMed]

D. Williams, Y. Zheng, F. Bao, and A. Elsheikh, “Fast segmentation of anterior segment optical coherence tomography images using graph cut,” Eye and Vision 2, 1 (2015).
[Crossref] [PubMed]

J. Novosel, G. Thepass, H. G. Lemij, J. F. de Boer, K. A. Vermeer, and L. J. van Vliet, “Loosely coupled level sets for simultaneous 3D retinal layer segmentation in optical coherence tomography,” Med. Image Anal. 26, 146–158 (2015).
[Crossref] [PubMed]

J. J. Hermans, K. Keune, A. van Loon, and P. D. Iedema, “An infrared spectroscopic study of the nature of zinc carboxylates in oil paintings,” J. Anal. At. Spectrom. 30, 1600–1608 (2015).
[Crossref]

D. Ciofini, M. Oujja, M. V. Canamares, S. Siano, and M. Castillejo, “Spectroscopic assessment of the UV laser removal of varnishes from painted surfaces,” Microchem. J. 124, 792–803 (2015).
[Crossref]

J. Striova, B. Salvadori, R. Fontana, A. Sansonetti, M. Barucci, E. Pampaloni, E. Marconi, L. Pezzati, and M. P. Colombini, “Optical and spectroscopic tools for evaluating Er:YAG laser removal of shellac varnish,” Stud. Conserv. 60, S91–S96 (2015).
[Crossref]

2014 (2)

G. Fresquet and J.-P. Piel, “Optical characterization and defect inspection for 3D stacked IC technology,” International Symposium on Microelectronics 2014, 000630 (2014).
[Crossref]

K. A. Vermeer, J. Mo, J. J. A. Weda, H. G. Lemij, and J. F. de Boer, “Depth-resolved model-based reconstruction of attenuation coefficients in optical coherence tomography,” Biomed. Opt. Express 5, 322–337 (2014).
[Crossref] [PubMed]

2012 (1)

T. R. G. Babu, S. S. Devi, and R. Venkatesh, “Automatic detection of glaucoma using optical coherence tomography image,” J. Appl. Sci. 12, 2128–2138 (2012).
[Crossref]

2011 (2)

S.-H. Kim, J.-H. Kim, and S.-W. Kang, “Nondestructive defect inspection for LCDs using optical coherence tomography,” Displays 32, 325–329 (2011).
[Crossref]

S. Lawman and H. Liang, “High precision dynamic multi-interface profilometry with optical coherence tomography,” Appl. Opt. 50, 6039–6048 (2011).
[Crossref] [PubMed]

2010 (1)

2008 (4)

P. Targowski, B. Rouba, M. Góra, L. Tyminska-Widmer, J. Marczak, and A. Kowalczyk, “Optical coherence tomography in art diagnostics and restoration,” Appl. Phys. A 92, 1–9 (2008).
[Crossref]

P. Pouli, I.-A. Paun, G. Bounos, S. Georgiou, and C. Fotakis, “The potential of UV femtosecond laser ablation for varnish removal in the restoration of painted works of art,” Applied Surface Science 254, 6875–6879 (2008).
[Crossref]

J. K. Delaney, E. R. de la Rie, M. Elias, L.-P. Sung, and K. M. Morales, “The role of varnishes in modifying light reflection from rough surfaces - a study of changes in light scattering caused by variations in varnish topography and development of a drying model,” Stud. Conserv. 53, 170–186 (2008).
[Crossref]

F. van der Lijn, T. den Heijer, M. M. Breteler, and W. J. Niessen, “Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts,” NeuroImage 43, 708–720 (2008).
[Crossref] [PubMed]

2007 (1)

G. Michalina, P. Targowski, A. Rycyk, and J. Marczak, “Varnish ablation control by optical coherence tomography,” Laser Chem. 2006, 10647 (2007).

2004 (2)

2000 (1)

J. Shi and J. Malik, “Normalized cuts and image segmentation,” IEEE Trans. Pattern Anal. Mach. Intell. 22, 888–905 (2000).
[Crossref]

1996 (1)

M. R. Hee, C. R. Baumal, C. A. Puliafito, J. S. Duker, E. Reichel, J. R. Wilkins, J. G. Coker, J. S. Schuman, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography of age-related macular degeneration and choroidal neovascularization,” Ophthalmology 103, 1260–1270 (1996).
[Crossref] [PubMed]

1987 (1)

E. R. de la Rie, “The influence of varnishes on the appearance of paintings,” Stud. Conserv. 32, 1–13 (1987).

1959 (1)

E. Dijkstra, “A note on two problems in connexion with graphs,” Numer. Math 1, 269–271 (1959).
[Crossref]

Abolghasemi, V.

Y. Dong, H. Lin, V. Abolghasemi, L. Gan, J. A. Zeitler, and Y.-C. Shen, “Investigating intra-tablet coating uniformity with spectral-domain optical coherence tomography,” J. Pharm. Sci. 106, 546–553 (2017).
[Crossref]

Babu, T. R. G.

T. R. G. Babu, S. S. Devi, and R. Venkatesh, “Automatic detection of glaucoma using optical coherence tomography image,” J. Appl. Sci. 12, 2128–2138 (2012).
[Crossref]

Bao, F.

D. Williams, Y. Zheng, F. Bao, and A. Elsheikh, “Fast segmentation of anterior segment optical coherence tomography images using graph cut,” Eye and Vision 2, 1 (2015).
[Crossref] [PubMed]

Barucci, M.

J. Striova, B. Salvadori, R. Fontana, A. Sansonetti, M. Barucci, E. Pampaloni, E. Marconi, L. Pezzati, and M. P. Colombini, “Optical and spectroscopic tools for evaluating Er:YAG laser removal of shellac varnish,” Stud. Conserv. 60, S91–S96 (2015).
[Crossref]

Baumal, C. R.

M. R. Hee, C. R. Baumal, C. A. Puliafito, J. S. Duker, E. Reichel, J. R. Wilkins, J. G. Coker, J. S. Schuman, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography of age-related macular degeneration and choroidal neovascularization,” Ophthalmology 103, 1260–1270 (1996).
[Crossref] [PubMed]

Bouma, B. E.

Bounos, G.

P. Pouli, I.-A. Paun, G. Bounos, S. Georgiou, and C. Fotakis, “The potential of UV femtosecond laser ablation for varnish removal in the restoration of painted works of art,” Applied Surface Science 254, 6875–6879 (2008).
[Crossref]

Breteler, M. M.

F. van der Lijn, T. den Heijer, M. M. Breteler, and W. J. Niessen, “Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts,” NeuroImage 43, 708–720 (2008).
[Crossref] [PubMed]

Canamares, M. V.

D. Ciofini, M. Oujja, M. V. Canamares, S. Siano, and M. Castillejo, “Spectroscopic assessment of the UV laser removal of varnishes from painted surfaces,” Microchem. J. 124, 792–803 (2015).
[Crossref]

Castillejo, M.

D. Ciofini, M. Oujja, M. V. Canamares, S. Siano, and M. Castillejo, “Spectroscopic assessment of the UV laser removal of varnishes from painted surfaces,” Microchem. J. 124, 792–803 (2015).
[Crossref]

Cense, B.

Chen, S.

L. Zhang, H. Kong, S. Liu, T. Wang, S. Chen, and M. Sonka, “Graph-based segmentation of abnormal nuclei in cervical cytology,” Comput. Med. Imaging Graphics 56, 38–48 (2017).
[Crossref]

Chen, T. C.

Cheung, C. S.

Chiu, S. J.

Ciofini, D.

D. Ciofini, M. Oujja, M. V. Canamares, S. Siano, and M. Castillejo, “Spectroscopic assessment of the UV laser removal of varnishes from painted surfaces,” Microchem. J. 124, 792–803 (2015).
[Crossref]

Coker, J. G.

M. R. Hee, C. R. Baumal, C. A. Puliafito, J. S. Duker, E. Reichel, J. R. Wilkins, J. G. Coker, J. S. Schuman, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography of age-related macular degeneration and choroidal neovascularization,” Ophthalmology 103, 1260–1270 (1996).
[Crossref] [PubMed]

Colombini, M. P.

J. Striova, B. Salvadori, R. Fontana, A. Sansonetti, M. Barucci, E. Pampaloni, E. Marconi, L. Pezzati, and M. P. Colombini, “Optical and spectroscopic tools for evaluating Er:YAG laser removal of shellac varnish,” Stud. Conserv. 60, S91–S96 (2015).
[Crossref]

de Boer, J. F.

de la Rie, E. R.

J. K. Delaney, E. R. de la Rie, M. Elias, L.-P. Sung, and K. M. Morales, “The role of varnishes in modifying light reflection from rough surfaces - a study of changes in light scattering caused by variations in varnish topography and development of a drying model,” Stud. Conserv. 53, 170–186 (2008).
[Crossref]

E. R. de la Rie, “The influence of varnishes on the appearance of paintings,” Stud. Conserv. 32, 1–13 (1987).

Delaney, J. K.

J. K. Delaney, E. R. de la Rie, M. Elias, L.-P. Sung, and K. M. Morales, “The role of varnishes in modifying light reflection from rough surfaces - a study of changes in light scattering caused by variations in varnish topography and development of a drying model,” Stud. Conserv. 53, 170–186 (2008).
[Crossref]

den Heijer, T.

F. van der Lijn, T. den Heijer, M. M. Breteler, and W. J. Niessen, “Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts,” NeuroImage 43, 708–720 (2008).
[Crossref] [PubMed]

Devi, S. S.

T. R. G. Babu, S. S. Devi, and R. Venkatesh, “Automatic detection of glaucoma using optical coherence tomography image,” J. Appl. Sci. 12, 2128–2138 (2012).
[Crossref]

Dijkstra, E.

E. Dijkstra, “A note on two problems in connexion with graphs,” Numer. Math 1, 269–271 (1959).
[Crossref]

Dillmann, C.

M. Lenz, C. Mazzon, C. Dillmann, N. C. Gerhardt, H. Welp, M. Prange, and M. R. Hofmann, “Spectral domain optical coherence tomography for non-destructive testing of protection coatings on metal substrates,” Appl. Sci. 7364 (2017).
[Crossref]

Dong, Y.

Y. Dong, H. Lin, V. Abolghasemi, L. Gan, J. A. Zeitler, and Y.-C. Shen, “Investigating intra-tablet coating uniformity with spectral-domain optical coherence tomography,” J. Pharm. Sci. 106, 546–553 (2017).
[Crossref]

Y. Dong, S. Lawman, Y. Zheng, D. Williams, J. Zhang, and Y.-C. Shen, “Nondestructive analysis of automotive paints with spectral domain optical coherence tomography,” Appl. Opt. 55, 3695–3700 (2016).
[Crossref] [PubMed]

Duker, J. S.

M. R. Hee, C. R. Baumal, C. A. Puliafito, J. S. Duker, E. Reichel, J. R. Wilkins, J. G. Coker, J. S. Schuman, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography of age-related macular degeneration and choroidal neovascularization,” Ophthalmology 103, 1260–1270 (1996).
[Crossref] [PubMed]

Elias, M.

J. K. Delaney, E. R. de la Rie, M. Elias, L.-P. Sung, and K. M. Morales, “The role of varnishes in modifying light reflection from rough surfaces - a study of changes in light scattering caused by variations in varnish topography and development of a drying model,” Stud. Conserv. 53, 170–186 (2008).
[Crossref]

Elsheikh, A.

D. Williams, Y. Zheng, F. Bao, and A. Elsheikh, “Fast segmentation of anterior segment optical coherence tomography images using graph cut,” Eye and Vision 2, 1 (2015).
[Crossref] [PubMed]

Farsiu, S.

Fontana, R.

J. Striova, B. Salvadori, R. Fontana, A. Sansonetti, M. Barucci, E. Pampaloni, E. Marconi, L. Pezzati, and M. P. Colombini, “Optical and spectroscopic tools for evaluating Er:YAG laser removal of shellac varnish,” Stud. Conserv. 60, S91–S96 (2015).
[Crossref]

Fotakis, C.

P. Pouli, I.-A. Paun, G. Bounos, S. Georgiou, and C. Fotakis, “The potential of UV femtosecond laser ablation for varnish removal in the restoration of painted works of art,” Applied Surface Science 254, 6875–6879 (2008).
[Crossref]

Fresquet, G.

G. Fresquet and J.-P. Piel, “Optical characterization and defect inspection for 3D stacked IC technology,” International Symposium on Microelectronics 2014, 000630 (2014).
[Crossref]

Fujimoto, J. G.

M. R. Hee, C. R. Baumal, C. A. Puliafito, J. S. Duker, E. Reichel, J. R. Wilkins, J. G. Coker, J. S. Schuman, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography of age-related macular degeneration and choroidal neovascularization,” Ophthalmology 103, 1260–1270 (1996).
[Crossref] [PubMed]

Gan, L.

Y. Dong, H. Lin, V. Abolghasemi, L. Gan, J. A. Zeitler, and Y.-C. Shen, “Investigating intra-tablet coating uniformity with spectral-domain optical coherence tomography,” J. Pharm. Sci. 106, 546–553 (2017).
[Crossref]

Georgiou, S.

P. Pouli, I.-A. Paun, G. Bounos, S. Georgiou, and C. Fotakis, “The potential of UV femtosecond laser ablation for varnish removal in the restoration of painted works of art,” Applied Surface Science 254, 6875–6879 (2008).
[Crossref]

Gerhardt, N. C.

M. Lenz, C. Mazzon, C. Dillmann, N. C. Gerhardt, H. Welp, M. Prange, and M. R. Hofmann, “Spectral domain optical coherence tomography for non-destructive testing of protection coatings on metal substrates,” Appl. Sci. 7364 (2017).
[Crossref]

Góra, M.

P. Targowski, B. Rouba, M. Góra, L. Tyminska-Widmer, J. Marczak, and A. Kowalczyk, “Optical coherence tomography in art diagnostics and restoration,” Appl. Phys. A 92, 1–9 (2008).
[Crossref]

Hee, M. R.

M. R. Hee, C. R. Baumal, C. A. Puliafito, J. S. Duker, E. Reichel, J. R. Wilkins, J. G. Coker, J. S. Schuman, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography of age-related macular degeneration and choroidal neovascularization,” Ophthalmology 103, 1260–1270 (1996).
[Crossref] [PubMed]

Hermans, J. J.

J. J. Hermans, K. Keune, A. van Loon, and P. D. Iedema, “An infrared spectroscopic study of the nature of zinc carboxylates in oil paintings,” J. Anal. At. Spectrom. 30, 1600–1608 (2015).
[Crossref]

Hillmann, D.

D. Hillmann, “Holoscopy,” Springer (2014).

Hofmann, M. R.

M. Lenz, C. Mazzon, C. Dillmann, N. C. Gerhardt, H. Welp, M. Prange, and M. R. Hofmann, “Spectral domain optical coherence tomography for non-destructive testing of protection coatings on metal substrates,” Appl. Sci. 7364 (2017).
[Crossref]

Hsu, I.-J.

M.-L. Yang, C.-W. Lu, I.-J. Hsu, and C. C. Yang, “The use of optical coherence tomography for monitoring the subsurface morphologies of archaic jades,” Archaeometry 46, 171–182 (2004).
[Crossref]

Iedema, P. D.

J. J. Hermans, K. Keune, A. van Loon, and P. D. Iedema, “An infrared spectroscopic study of the nature of zinc carboxylates in oil paintings,” J. Anal. At. Spectrom. 30, 1600–1608 (2015).
[Crossref]

Izatt, J. A.

Kaba, D.

Kalkman, J.

J. Kalkman, “Fourier-domain optical coherence tomography signal analysis and numerical modeling,” Int. J. Opt. 229586067 (2017).

Kang, S.-W.

S.-H. Kim, J.-H. Kim, and S.-W. Kang, “Nondestructive defect inspection for LCDs using optical coherence tomography,” Displays 32, 325–329 (2011).
[Crossref]

Keune, K.

J. J. Hermans, K. Keune, A. van Loon, and P. D. Iedema, “An infrared spectroscopic study of the nature of zinc carboxylates in oil paintings,” J. Anal. At. Spectrom. 30, 1600–1608 (2015).
[Crossref]

Kim, J.-H.

S.-H. Kim, J.-H. Kim, and S.-W. Kang, “Nondestructive defect inspection for LCDs using optical coherence tomography,” Displays 32, 325–329 (2011).
[Crossref]

Kim, S.-H.

S.-H. Kim, J.-H. Kim, and S.-W. Kang, “Nondestructive defect inspection for LCDs using optical coherence tomography,” Displays 32, 325–329 (2011).
[Crossref]

Kong, H.

L. Zhang, H. Kong, S. Liu, T. Wang, S. Chen, and M. Sonka, “Graph-based segmentation of abnormal nuclei in cervical cytology,” Comput. Med. Imaging Graphics 56, 38–48 (2017).
[Crossref]

Kowalczyk, A.

P. Targowski, B. Rouba, M. Góra, L. Tyminska-Widmer, J. Marczak, and A. Kowalczyk, “Optical coherence tomography in art diagnostics and restoration,” Appl. Phys. A 92, 1–9 (2008).
[Crossref]

Lawman, S.

Lemij, H. G.

J. Novosel, G. Thepass, H. G. Lemij, J. F. de Boer, K. A. Vermeer, and L. J. van Vliet, “Loosely coupled level sets for simultaneous 3D retinal layer segmentation in optical coherence tomography,” Med. Image Anal. 26, 146–158 (2015).
[Crossref] [PubMed]

K. A. Vermeer, J. Mo, J. J. A. Weda, H. G. Lemij, and J. F. de Boer, “Depth-resolved model-based reconstruction of attenuation coefficients in optical coherence tomography,” Biomed. Opt. Express 5, 322–337 (2014).
[Crossref] [PubMed]

Lenz, M.

M. Lenz, C. Mazzon, C. Dillmann, N. C. Gerhardt, H. Welp, M. Prange, and M. R. Hofmann, “Spectral domain optical coherence tomography for non-destructive testing of protection coatings on metal substrates,” Appl. Sci. 7364 (2017).
[Crossref]

Li, X. T.

Li, Y.

Liang, H.

Lin, H.

Y. Dong, H. Lin, V. Abolghasemi, L. Gan, J. A. Zeitler, and Y.-C. Shen, “Investigating intra-tablet coating uniformity with spectral-domain optical coherence tomography,” J. Pharm. Sci. 106, 546–553 (2017).
[Crossref]

Liu, S.

L. Zhang, H. Kong, S. Liu, T. Wang, S. Chen, and M. Sonka, “Graph-based segmentation of abnormal nuclei in cervical cytology,” Comput. Med. Imaging Graphics 56, 38–48 (2017).
[Crossref]

Liu, X.

Lu, C.-W.

M.-L. Yang, C.-W. Lu, I.-J. Hsu, and C. C. Yang, “The use of optical coherence tomography for monitoring the subsurface morphologies of archaic jades,” Archaeometry 46, 171–182 (2004).
[Crossref]

Malik, J.

J. Shi and J. Malik, “Normalized cuts and image segmentation,” IEEE Trans. Pattern Anal. Mach. Intell. 22, 888–905 (2000).
[Crossref]

Marconi, E.

J. Striova, B. Salvadori, R. Fontana, A. Sansonetti, M. Barucci, E. Pampaloni, E. Marconi, L. Pezzati, and M. P. Colombini, “Optical and spectroscopic tools for evaluating Er:YAG laser removal of shellac varnish,” Stud. Conserv. 60, S91–S96 (2015).
[Crossref]

Marczak, J.

P. Targowski, B. Rouba, M. Góra, L. Tyminska-Widmer, J. Marczak, and A. Kowalczyk, “Optical coherence tomography in art diagnostics and restoration,” Appl. Phys. A 92, 1–9 (2008).
[Crossref]

G. Michalina, P. Targowski, A. Rycyk, and J. Marczak, “Varnish ablation control by optical coherence tomography,” Laser Chem. 2006, 10647 (2007).

Mazzon, C.

M. Lenz, C. Mazzon, C. Dillmann, N. C. Gerhardt, H. Welp, M. Prange, and M. R. Hofmann, “Spectral domain optical coherence tomography for non-destructive testing of protection coatings on metal substrates,” Appl. Sci. 7364 (2017).
[Crossref]

Michalina, G.

G. Michalina, P. Targowski, A. Rycyk, and J. Marczak, “Varnish ablation control by optical coherence tomography,” Laser Chem. 2006, 10647 (2007).

Mo, J.

Morales, K. M.

J. K. Delaney, E. R. de la Rie, M. Elias, L.-P. Sung, and K. M. Morales, “The role of varnishes in modifying light reflection from rough surfaces - a study of changes in light scattering caused by variations in varnish topography and development of a drying model,” Stud. Conserv. 53, 170–186 (2008).
[Crossref]

Nassif, N. A.

Nicholas, P.

Niessen, W. J.

F. van der Lijn, T. den Heijer, M. M. Breteler, and W. J. Niessen, “Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts,” NeuroImage 43, 708–720 (2008).
[Crossref] [PubMed]

Novosel, J.

J. Novosel, G. Thepass, H. G. Lemij, J. F. de Boer, K. A. Vermeer, and L. J. van Vliet, “Loosely coupled level sets for simultaneous 3D retinal layer segmentation in optical coherence tomography,” Med. Image Anal. 26, 146–158 (2015).
[Crossref] [PubMed]

Oujja, M.

D. Ciofini, M. Oujja, M. V. Canamares, S. Siano, and M. Castillejo, “Spectroscopic assessment of the UV laser removal of varnishes from painted surfaces,” Microchem. J. 124, 792–803 (2015).
[Crossref]

Pampaloni, E.

J. Striova, B. Salvadori, R. Fontana, A. Sansonetti, M. Barucci, E. Pampaloni, E. Marconi, L. Pezzati, and M. P. Colombini, “Optical and spectroscopic tools for evaluating Er:YAG laser removal of shellac varnish,” Stud. Conserv. 60, S91–S96 (2015).
[Crossref]

Park, B. H.

Paun, I.-A.

P. Pouli, I.-A. Paun, G. Bounos, S. Georgiou, and C. Fotakis, “The potential of UV femtosecond laser ablation for varnish removal in the restoration of painted works of art,” Applied Surface Science 254, 6875–6879 (2008).
[Crossref]

Pezzati, L.

J. Striova, B. Salvadori, R. Fontana, A. Sansonetti, M. Barucci, E. Pampaloni, E. Marconi, L. Pezzati, and M. P. Colombini, “Optical and spectroscopic tools for evaluating Er:YAG laser removal of shellac varnish,” Stud. Conserv. 60, S91–S96 (2015).
[Crossref]

Piel, J.-P.

G. Fresquet and J.-P. Piel, “Optical characterization and defect inspection for 3D stacked IC technology,” International Symposium on Microelectronics 2014, 000630 (2014).
[Crossref]

Pierce, M. C.

Pouli, P.

P. Pouli, I.-A. Paun, G. Bounos, S. Georgiou, and C. Fotakis, “The potential of UV femtosecond laser ablation for varnish removal in the restoration of painted works of art,” Applied Surface Science 254, 6875–6879 (2008).
[Crossref]

Prange, M.

M. Lenz, C. Mazzon, C. Dillmann, N. C. Gerhardt, H. Welp, M. Prange, and M. R. Hofmann, “Spectral domain optical coherence tomography for non-destructive testing of protection coatings on metal substrates,” Appl. Sci. 7364 (2017).
[Crossref]

Puliafito, C. A.

M. R. Hee, C. R. Baumal, C. A. Puliafito, J. S. Duker, E. Reichel, J. R. Wilkins, J. G. Coker, J. S. Schuman, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography of age-related macular degeneration and choroidal neovascularization,” Ophthalmology 103, 1260–1270 (1996).
[Crossref] [PubMed]

Reichel, E.

M. R. Hee, C. R. Baumal, C. A. Puliafito, J. S. Duker, E. Reichel, J. R. Wilkins, J. G. Coker, J. S. Schuman, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography of age-related macular degeneration and choroidal neovascularization,” Ophthalmology 103, 1260–1270 (1996).
[Crossref] [PubMed]

Rouba, B.

P. Targowski, B. Rouba, M. Góra, L. Tyminska-Widmer, J. Marczak, and A. Kowalczyk, “Optical coherence tomography in art diagnostics and restoration,” Appl. Phys. A 92, 1–9 (2008).
[Crossref]

Rycyk, A.

G. Michalina, P. Targowski, A. Rycyk, and J. Marczak, “Varnish ablation control by optical coherence tomography,” Laser Chem. 2006, 10647 (2007).

Salazar-Gonzalez, A. G.

Salvadori, B.

J. Striova, B. Salvadori, R. Fontana, A. Sansonetti, M. Barucci, E. Pampaloni, E. Marconi, L. Pezzati, and M. P. Colombini, “Optical and spectroscopic tools for evaluating Er:YAG laser removal of shellac varnish,” Stud. Conserv. 60, S91–S96 (2015).
[Crossref]

Sansonetti, A.

J. Striova, B. Salvadori, R. Fontana, A. Sansonetti, M. Barucci, E. Pampaloni, E. Marconi, L. Pezzati, and M. P. Colombini, “Optical and spectroscopic tools for evaluating Er:YAG laser removal of shellac varnish,” Stud. Conserv. 60, S91–S96 (2015).
[Crossref]

Schuman, J. S.

M. R. Hee, C. R. Baumal, C. A. Puliafito, J. S. Duker, E. Reichel, J. R. Wilkins, J. G. Coker, J. S. Schuman, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography of age-related macular degeneration and choroidal neovascularization,” Ophthalmology 103, 1260–1270 (1996).
[Crossref] [PubMed]

Shen, Y.-C.

Y. Dong, H. Lin, V. Abolghasemi, L. Gan, J. A. Zeitler, and Y.-C. Shen, “Investigating intra-tablet coating uniformity with spectral-domain optical coherence tomography,” J. Pharm. Sci. 106, 546–553 (2017).
[Crossref]

Y. Dong, S. Lawman, Y. Zheng, D. Williams, J. Zhang, and Y.-C. Shen, “Nondestructive analysis of automotive paints with spectral domain optical coherence tomography,” Appl. Opt. 55, 3695–3700 (2016).
[Crossref] [PubMed]

Shi, J.

J. Shi and J. Malik, “Normalized cuts and image segmentation,” IEEE Trans. Pattern Anal. Mach. Intell. 22, 888–905 (2000).
[Crossref]

Siano, S.

D. Ciofini, M. Oujja, M. V. Canamares, S. Siano, and M. Castillejo, “Spectroscopic assessment of the UV laser removal of varnishes from painted surfaces,” Microchem. J. 124, 792–803 (2015).
[Crossref]

Sonka, M.

L. Zhang, H. Kong, S. Liu, T. Wang, S. Chen, and M. Sonka, “Graph-based segmentation of abnormal nuclei in cervical cytology,” Comput. Med. Imaging Graphics 56, 38–48 (2017).
[Crossref]

Spring, M.

Striova, J.

J. Striova, B. Salvadori, R. Fontana, A. Sansonetti, M. Barucci, E. Pampaloni, E. Marconi, L. Pezzati, and M. P. Colombini, “Optical and spectroscopic tools for evaluating Er:YAG laser removal of shellac varnish,” Stud. Conserv. 60, S91–S96 (2015).
[Crossref]

Sung, L.-P.

J. K. Delaney, E. R. de la Rie, M. Elias, L.-P. Sung, and K. M. Morales, “The role of varnishes in modifying light reflection from rough surfaces - a study of changes in light scattering caused by variations in varnish topography and development of a drying model,” Stud. Conserv. 53, 170–186 (2008).
[Crossref]

Swanson, E. A.

M. R. Hee, C. R. Baumal, C. A. Puliafito, J. S. Duker, E. Reichel, J. R. Wilkins, J. G. Coker, J. S. Schuman, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography of age-related macular degeneration and choroidal neovascularization,” Ophthalmology 103, 1260–1270 (1996).
[Crossref] [PubMed]

Targowski, P.

P. Targowski, B. Rouba, M. Góra, L. Tyminska-Widmer, J. Marczak, and A. Kowalczyk, “Optical coherence tomography in art diagnostics and restoration,” Appl. Phys. A 92, 1–9 (2008).
[Crossref]

G. Michalina, P. Targowski, A. Rycyk, and J. Marczak, “Varnish ablation control by optical coherence tomography,” Laser Chem. 2006, 10647 (2007).

Tearney, G. J.

Thepass, G.

J. Novosel, G. Thepass, H. G. Lemij, J. F. de Boer, K. A. Vermeer, and L. J. van Vliet, “Loosely coupled level sets for simultaneous 3D retinal layer segmentation in optical coherence tomography,” Med. Image Anal. 26, 146–158 (2015).
[Crossref] [PubMed]

Toth, C. A.

Tyminska-Widmer, L.

P. Targowski, B. Rouba, M. Góra, L. Tyminska-Widmer, J. Marczak, and A. Kowalczyk, “Optical coherence tomography in art diagnostics and restoration,” Appl. Phys. A 92, 1–9 (2008).
[Crossref]

van der Lijn, F.

F. van der Lijn, T. den Heijer, M. M. Breteler, and W. J. Niessen, “Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts,” NeuroImage 43, 708–720 (2008).
[Crossref] [PubMed]

van Loon, A.

J. J. Hermans, K. Keune, A. van Loon, and P. D. Iedema, “An infrared spectroscopic study of the nature of zinc carboxylates in oil paintings,” J. Anal. At. Spectrom. 30, 1600–1608 (2015).
[Crossref]

van Vliet, L. J.

J. Novosel, G. Thepass, H. G. Lemij, J. F. de Boer, K. A. Vermeer, and L. J. van Vliet, “Loosely coupled level sets for simultaneous 3D retinal layer segmentation in optical coherence tomography,” Med. Image Anal. 26, 146–158 (2015).
[Crossref] [PubMed]

Venkatesh, R.

T. R. G. Babu, S. S. Devi, and R. Venkatesh, “Automatic detection of glaucoma using optical coherence tomography image,” J. Appl. Sci. 12, 2128–2138 (2012).
[Crossref]

Vermeer, K. A.

J. Novosel, G. Thepass, H. G. Lemij, J. F. de Boer, K. A. Vermeer, and L. J. van Vliet, “Loosely coupled level sets for simultaneous 3D retinal layer segmentation in optical coherence tomography,” Med. Image Anal. 26, 146–158 (2015).
[Crossref] [PubMed]

K. A. Vermeer, J. Mo, J. J. A. Weda, H. G. Lemij, and J. F. de Boer, “Depth-resolved model-based reconstruction of attenuation coefficients in optical coherence tomography,” Biomed. Opt. Express 5, 322–337 (2014).
[Crossref] [PubMed]

Wang, C.

Wang, T.

L. Zhang, H. Kong, S. Liu, T. Wang, S. Chen, and M. Sonka, “Graph-based segmentation of abnormal nuclei in cervical cytology,” Comput. Med. Imaging Graphics 56, 38–48 (2017).
[Crossref]

Wang, Y.

Weda, J. J. A.

Welp, H.

M. Lenz, C. Mazzon, C. Dillmann, N. C. Gerhardt, H. Welp, M. Prange, and M. R. Hofmann, “Spectral domain optical coherence tomography for non-destructive testing of protection coatings on metal substrates,” Appl. Sci. 7364 (2017).
[Crossref]

Wilkins, J. R.

M. R. Hee, C. R. Baumal, C. A. Puliafito, J. S. Duker, E. Reichel, J. R. Wilkins, J. G. Coker, J. S. Schuman, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography of age-related macular degeneration and choroidal neovascularization,” Ophthalmology 103, 1260–1270 (1996).
[Crossref] [PubMed]

Williams, D.

Y. Dong, S. Lawman, Y. Zheng, D. Williams, J. Zhang, and Y.-C. Shen, “Nondestructive analysis of automotive paints with spectral domain optical coherence tomography,” Appl. Opt. 55, 3695–3700 (2016).
[Crossref] [PubMed]

D. Williams, Y. Zheng, F. Bao, and A. Elsheikh, “Fast segmentation of anterior segment optical coherence tomography images using graph cut,” Eye and Vision 2, 1 (2015).
[Crossref] [PubMed]

Yang, C. C.

M.-L. Yang, C.-W. Lu, I.-J. Hsu, and C. C. Yang, “The use of optical coherence tomography for monitoring the subsurface morphologies of archaic jades,” Archaeometry 46, 171–182 (2004).
[Crossref]

Yang, M.-L.

M.-L. Yang, C.-W. Lu, I.-J. Hsu, and C. C. Yang, “The use of optical coherence tomography for monitoring the subsurface morphologies of archaic jades,” Archaeometry 46, 171–182 (2004).
[Crossref]

Yun, S. H.

Zeitler, J. A.

Y. Dong, H. Lin, V. Abolghasemi, L. Gan, J. A. Zeitler, and Y.-C. Shen, “Investigating intra-tablet coating uniformity with spectral-domain optical coherence tomography,” J. Pharm. Sci. 106, 546–553 (2017).
[Crossref]

Zhang, J.

Zhang, L.

L. Zhang, H. Kong, S. Liu, T. Wang, S. Chen, and M. Sonka, “Graph-based segmentation of abnormal nuclei in cervical cytology,” Comput. Med. Imaging Graphics 56, 38–48 (2017).
[Crossref]

Zheng, Y.

Y. Dong, S. Lawman, Y. Zheng, D. Williams, J. Zhang, and Y.-C. Shen, “Nondestructive analysis of automotive paints with spectral domain optical coherence tomography,” Appl. Opt. 55, 3695–3700 (2016).
[Crossref] [PubMed]

D. Williams, Y. Zheng, F. Bao, and A. Elsheikh, “Fast segmentation of anterior segment optical coherence tomography images using graph cut,” Eye and Vision 2, 1 (2015).
[Crossref] [PubMed]

Zhu, H.

Appl. Opt. (2)

Appl. Phys. A (1)

P. Targowski, B. Rouba, M. Góra, L. Tyminska-Widmer, J. Marczak, and A. Kowalczyk, “Optical coherence tomography in art diagnostics and restoration,” Appl. Phys. A 92, 1–9 (2008).
[Crossref]

Appl. Sci. (1)

M. Lenz, C. Mazzon, C. Dillmann, N. C. Gerhardt, H. Welp, M. Prange, and M. R. Hofmann, “Spectral domain optical coherence tomography for non-destructive testing of protection coatings on metal substrates,” Appl. Sci. 7364 (2017).
[Crossref]

Applied Surface Science (1)

P. Pouli, I.-A. Paun, G. Bounos, S. Georgiou, and C. Fotakis, “The potential of UV femtosecond laser ablation for varnish removal in the restoration of painted works of art,” Applied Surface Science 254, 6875–6879 (2008).
[Crossref]

Archaeometry (1)

M.-L. Yang, C.-W. Lu, I.-J. Hsu, and C. C. Yang, “The use of optical coherence tomography for monitoring the subsurface morphologies of archaic jades,” Archaeometry 46, 171–182 (2004).
[Crossref]

Biomed. Opt. Express (1)

Comput. Med. Imaging Graphics (1)

L. Zhang, H. Kong, S. Liu, T. Wang, S. Chen, and M. Sonka, “Graph-based segmentation of abnormal nuclei in cervical cytology,” Comput. Med. Imaging Graphics 56, 38–48 (2017).
[Crossref]

Displays (1)

S.-H. Kim, J.-H. Kim, and S.-W. Kang, “Nondestructive defect inspection for LCDs using optical coherence tomography,” Displays 32, 325–329 (2011).
[Crossref]

Eye and Vision (1)

D. Williams, Y. Zheng, F. Bao, and A. Elsheikh, “Fast segmentation of anterior segment optical coherence tomography images using graph cut,” Eye and Vision 2, 1 (2015).
[Crossref] [PubMed]

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

J. Shi and J. Malik, “Normalized cuts and image segmentation,” IEEE Trans. Pattern Anal. Mach. Intell. 22, 888–905 (2000).
[Crossref]

Int. J. Opt. (1)

J. Kalkman, “Fourier-domain optical coherence tomography signal analysis and numerical modeling,” Int. J. Opt. 229586067 (2017).

International Symposium on Microelectronics (1)

G. Fresquet and J.-P. Piel, “Optical characterization and defect inspection for 3D stacked IC technology,” International Symposium on Microelectronics 2014, 000630 (2014).
[Crossref]

J. Anal. At. Spectrom. (1)

J. J. Hermans, K. Keune, A. van Loon, and P. D. Iedema, “An infrared spectroscopic study of the nature of zinc carboxylates in oil paintings,” J. Anal. At. Spectrom. 30, 1600–1608 (2015).
[Crossref]

J. Appl. Sci. (1)

T. R. G. Babu, S. S. Devi, and R. Venkatesh, “Automatic detection of glaucoma using optical coherence tomography image,” J. Appl. Sci. 12, 2128–2138 (2012).
[Crossref]

J. Pharm. Sci. (1)

Y. Dong, H. Lin, V. Abolghasemi, L. Gan, J. A. Zeitler, and Y.-C. Shen, “Investigating intra-tablet coating uniformity with spectral-domain optical coherence tomography,” J. Pharm. Sci. 106, 546–553 (2017).
[Crossref]

Laser Chem. (1)

G. Michalina, P. Targowski, A. Rycyk, and J. Marczak, “Varnish ablation control by optical coherence tomography,” Laser Chem. 2006, 10647 (2007).

Med. Image Anal. (1)

J. Novosel, G. Thepass, H. G. Lemij, J. F. de Boer, K. A. Vermeer, and L. J. van Vliet, “Loosely coupled level sets for simultaneous 3D retinal layer segmentation in optical coherence tomography,” Med. Image Anal. 26, 146–158 (2015).
[Crossref] [PubMed]

Microchem. J. (1)

D. Ciofini, M. Oujja, M. V. Canamares, S. Siano, and M. Castillejo, “Spectroscopic assessment of the UV laser removal of varnishes from painted surfaces,” Microchem. J. 124, 792–803 (2015).
[Crossref]

NeuroImage (1)

F. van der Lijn, T. den Heijer, M. M. Breteler, and W. J. Niessen, “Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts,” NeuroImage 43, 708–720 (2008).
[Crossref] [PubMed]

Numer. Math (1)

E. Dijkstra, “A note on two problems in connexion with graphs,” Numer. Math 1, 269–271 (1959).
[Crossref]

Ophthalmology (1)

M. R. Hee, C. R. Baumal, C. A. Puliafito, J. S. Duker, E. Reichel, J. R. Wilkins, J. G. Coker, J. S. Schuman, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography of age-related macular degeneration and choroidal neovascularization,” Ophthalmology 103, 1260–1270 (1996).
[Crossref] [PubMed]

Opt. Express (4)

Stud. Conserv. (3)

J. K. Delaney, E. R. de la Rie, M. Elias, L.-P. Sung, and K. M. Morales, “The role of varnishes in modifying light reflection from rough surfaces - a study of changes in light scattering caused by variations in varnish topography and development of a drying model,” Stud. Conserv. 53, 170–186 (2008).
[Crossref]

E. R. de la Rie, “The influence of varnishes on the appearance of paintings,” Stud. Conserv. 32, 1–13 (1987).

J. Striova, B. Salvadori, R. Fontana, A. Sansonetti, M. Barucci, E. Pampaloni, E. Marconi, L. Pezzati, and M. P. Colombini, “Optical and spectroscopic tools for evaluating Er:YAG laser removal of shellac varnish,” Stud. Conserv. 60, S91–S96 (2015).
[Crossref]

Other (1)

D. Hillmann, “Holoscopy,” Springer (2014).

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Figures (8)

Fig. 1
Fig. 1 Schematic overview of our image segmentation algorithm. First, we perform a graph based segmentation (top row) that is refined with the matching layer attenuation coefficient segmentation algorithm (bottom row). All segmentation steps are performed on the OCT attenuation coefficient image.
Fig. 2
Fig. 2 Schematic overview of the implementation of the MLAS algorithm for a 2 layer AC OCT image. The upper row shows the segmentation of the upper interface (B1). (a) Initial segmentation results. (b) The centerline ΔB1,2 between B1 and B2 is determined. The resulting indices (ΔB1,2) are used to determine μ 1 ¯ . (c) Boundary B1 is shifted upwards, resulting in repositioned interface B 1 . (d) Interface B10 is shifted down until it detects a pixel value with an μ ¯ j , the final position of B 1 is the resegmented boundary. The second row of the figure (e, f, g, h) shows the repositioning of the second interface (B2) and is performed similar to the first interface. The approach is repeated for every interface detected by GBS. The orange interface (B3) denotes the required virtual interface at the bottom of the image.
Fig. 3
Fig. 3 (a) Simulated OCT image of a three-layered sample. The image is plotted in logarithmic intensity scale. (b) AC image based on (a). (c) Single A-line OCT intensity profile at the position indicated by the vertical bar in (a). (d) The AC profile at the position indicated by the vertical bar in (b). The horizontal bars correspond to the theoretical AC used as input for the simulation.
Fig. 4
Fig. 4 (a) Segmentation of a first interface in a simulated OCT image. GBS (yellow) segmentation is refined by the MLAS algorithm (magenta). (b) Segmentation of the second interface in the sample by the GBS (yellow) and MLAS algorithm (magenta).
Fig. 5
Fig. 5 Performance of GBS and MLAS for segmentation of the first interface in the simulated OCT images. The mean absolute segmentation error (MAE) for the top interface is plotted as a function of the input thickness of the top layer. The errorbars indicate the mean absolute deviation (MAD) of the mean absolute segmentation error.
Fig. 6
Fig. 6 Performance of GBS and MLAS for segmentation of the corrugated surface of a wood substrate. Box (1–3) indicate the regions of interest that are compared in Table 1.
Fig. 7
Fig. 7 (a) Segmentation of upper and lower interface of a single varnish layer on a wooden substrate. (b) Segmentation of 3 interfaces of two varnish layers of a 17th century historical painting.
Fig. 8
Fig. 8 Damaged transparent varnish layer on wood substrate. (a) Image of the object. (b) segmented Bscan in the image cube. (c) Enface projection of the varnish thickness map. (d) Varnish layer separated from the underlying wood substrate.

Tables (1)

Tables Icon

Table 1 overview of the segmentation results. MAE (pixels) is the mean absolute error. MAD (pixels) is the mean absolute deviation of the respective MAE values.

Equations (3)

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

Δ B j , j + 1 [ i , z ] = B j [ i , z ] + B j + 1 [ i , z ] 2 ,
μ ¯ j = 1 N i = 1 N ( M ( Δ B j , j + 1 [ i , z ] ) ) ,
σ j = 1 N 1 i = 1 N ( μ j [ i ] μ ¯ j ) 2 ,

Metrics