Abstract

Despeckling optical coherence tomograms from the human retina is a fundamental step to a better diagnosis or as a preprocessing stage for retinal layer segmentation. Both of these applications are particularly important in monitoring the progression of retinal disorders. In this study we propose a new formulation for a well-known nonlinear complex diffusion filter. A regularization factor is now made to be dependent on data, and the process itself is now an adaptive one. Experimental results making use of synthetic data show the good performance of the proposed formulation by achieving better quantitative results and increasing computation speed.

© 2010 OSA

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2008 (2)

A. M. Bagci, M. Shahidi, R. Ansari, M. Blair, N. P. Blair, and R. Zelkha, “Thickness profiles of retinal layers by optical coherence tomography image segmentation,” Am. J. Ophthalmol. 146(5), 679–687 (2008).
[CrossRef] [PubMed]

O. Tan, G. Li, A. T. H. Lu, R. Varma, D. Huang, and Advanced Imaging for Glaucoma Study Group, “Mapping of macular substructures with optical coherence tomography for glaucoma diagnosis,” Ophthalmology 115(6), 949–956 (2008).
[CrossRef]

2007 (5)

T. M. Jørgensen, J. Thomadsen, U. Christensen, W. Soliman, and B. Sander, “Enhancing the signal-to-noise ratio in ophthalmic optical coherence tomography by image registration--method and clinical examples,” J. Biomed. Opt. 12(4), 041208 (2007).
[CrossRef] [PubMed]

M. Baroni, P. Fortunato, and A. La Torre, “Towards quantitative analysis of retinal features in optical coherence tomography,” Med. Eng. Phys. 29(4), 432–441 (2007).
[CrossRef]

H. M. Salinas and D. C. Fernández, “Comparison of PDE-based nonlinear diffusion approaches for image enhancement and denoising in optical coherence tomography,” IEEE Trans. Med. Imaging 26(6), 761–771 (2007).
[CrossRef] [PubMed]

A. Ozcan, A. Bilenca, A. E. Desjardins, B. E. Bouma, and G. J. Tearney, “Speckle reduction in optical coherence tomography images using digital filtering,” J. Opt. Soc. Am. A 24(7), 1901–1910 (2007).
[CrossRef]

P. Puvanathasan and K. Bizheva, “Speckle noise reduction algorithm for optical coherence tomography based on interval type II fuzzy set,” Opt. Express 15(24), 15747–15758 (2007).
[CrossRef] [PubMed]

2005 (5)

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

H. Ishikawa, D. M. Stein, G. Wollstein, S. Beaton, J. G. Fujimoto, and J. S. Schuman, “Macular segmentation with optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 46(6), 2012–2017 (2005).
[CrossRef] [PubMed]

J. Kim, D. T. Miller, E. Kim, S. Oh, J. Oh, and T. E. Milner, “Optical coherence tomography speckle reduction by a partially spatially coherent source,” J. Biomed. Opt. 10(6), 064034 (2005).
[CrossRef]

M. Shahidi, Z. Wang, and R. Zelkha, “Quantitative thickness measurement of retinal layers imaged by optical coherence tomography,” Am. J. Ophthalmol. 139(6), 1056–1061 (2005).
[CrossRef] [PubMed]

B. Sander, M. Larsen, L. Thrane, J. L. Hougaard, and T. M. Jørgensen, “Enhanced optical coherence tomography imaging by multiple scan averaging,” Br. J. Ophthalmol. 89(2), 207–212 (2005).
[CrossRef] [PubMed]

2004 (1)

G. Gilboa, N. Sochen, and Y. Y. Zeevi, “Image enhancement and denoising by complex diffusion processes,” IEEE Trans. Pattern Anal. Mach. Intell. 26(8), 1020–1036 (2004).
[CrossRef]

2003 (2)

M. Pircher, E. Gotzinger, R. Leitgeb, A. F. Fercher, and C. K. Hitzenberger, “Speckle reduction in optical coherence tomography by frequency compounding,” J. Biomed. Opt. 8(3), 565–569 (2003).
[CrossRef] [PubMed]

N. Iftimia, B. E. Bouma, and G. J. Tearney, “Speckle reduction in optical coherence tomography by “path length encoded” angular compounding,” J. Biomed. Opt. 8(2), 260–263 (2003).
[CrossRef] [PubMed]

2001 (1)

W. Drexler, U. Morgner, R. K. Ghanta, F. X. Kärtner, J. S. Schuman, and J. G. Fujimoto, “Ultrahigh-resolution ophthalmic optical coherence tomography,” Nat. Med. 7(4), 502–507 (2001).
[CrossRef] [PubMed]

2000 (2)

J. Rogowska and M. E. Brezinski, “Evaluation of the adaptive speckle suppression filter for coronary optical coherence tomography imaging,” IEEE Trans. Med. Imaging 19(12), 1261–1266 (2000).
[CrossRef]

M. Bashkansky and J. Reintjes, “Statistics and reduction of speckle in optical coherence tomography,” Opt. Lett. 25(8), 545–547 (2000).
[CrossRef]

1999 (1)

K. M. Yung, S. L. Lee, and J. M. Schmitt, “Phase-domain processing of optical coherence tomography images,” J. Biomed. Opt. 4, 125–136 (1999).
[CrossRef]

1998 (2)

J. M. Schmitt, “Restoration of optical coherence images of living tissue using the clean algorithm,” J. Biomed. Opt. 3, 66–75 (1998).
[CrossRef]

S. H. Xiang, L. Zhou, and J. M. Schmitt, “Speckle noise reduction for optical coherence tomography,” Proc. SPIE 3196, 79–88 (1998).
[CrossRef]

1997 (1)

J. M. Schmitt, “Array detection for speckle reduction in optical coherence microscopy,” Phys. Med. Biol. 42(7), 1427–1439 (1997).
[CrossRef] [PubMed]

1995 (2)

1992 (1)

A. J. Healey, S. Leeman, and F. Forsberg, “Turning off speckle,” Acoust. Imaging 19, 433–437 (1992).
[CrossRef]

1990 (1)

P. Perona and J. Malik, “Scale-space and edge detection using anisotropic diffusion,” IEEE Trans. Pattern Anal. Mach. Intell. 12, 629–639 (1990).
[CrossRef]

1987 (1)

R. Bernstein, “Adaptive nonlinear filters for simultaneous removal of different kinds of noise in images,” IEEE Trans. Circ. Syst. 34, 1275–1291 (1987).
[CrossRef]

1985 (2)

P. Shankar and V. Newhouse, “Speckle reduction with improved resolution in ultrasound images,” IEEE Trans. Sonics Ultrason. SU-32, 537–543 (1985).

D. Kuan, A. Sawchuk, T. Strand, and P. Chavel, “Adaptive noise smoothing filter for images with signal-dependent noise,” IEEE Trans. Pattern Anal. Mach. Intell. 7, 165–177 (1985).
[CrossRef] [PubMed]

1983 (1)

R. Wagner, S. Smith, J. Sandrik, and H. Lopez, “Statistics of speckle in ultrasound b-scans,” IEEE Trans. Sonics Ultrason. 30, 156–163 (1983).
[CrossRef]

1981 (1)

J. Lee, “Speckle analysis and smoothing of synthetic aperture radar images,” Comput. Graph. Image Process. 17, 24–32 (1981).
[CrossRef]

1979 (1)

J. G. Abbott and F. L. Thurstone, “Acoustic speckle: theory and experimental analysis,” Ultrason. Imaging 1(4), 303–324 (1979).
[CrossRef] [PubMed]

1978 (1)

C. Burckhardt, “Speckle in ultrasound b-mode scans,” IEEE Trans. Sonics Ultrason. 25, 1–6 (1978).
[CrossRef]

1976 (1)

Abbott, J. G.

J. G. Abbott and F. L. Thurstone, “Acoustic speckle: theory and experimental analysis,” Ultrason. Imaging 1(4), 303–324 (1979).
[CrossRef] [PubMed]

Ansari, R.

A. M. Bagci, M. Shahidi, R. Ansari, M. Blair, N. P. Blair, and R. Zelkha, “Thickness profiles of retinal layers by optical coherence tomography image segmentation,” Am. J. Ophthalmol. 146(5), 679–687 (2008).
[CrossRef] [PubMed]

Bagci, A. M.

A. M. Bagci, M. Shahidi, R. Ansari, M. Blair, N. P. Blair, and R. Zelkha, “Thickness profiles of retinal layers by optical coherence tomography image segmentation,” Am. J. Ophthalmol. 146(5), 679–687 (2008).
[CrossRef] [PubMed]

Baroni, M.

M. Baroni, P. Fortunato, and A. La Torre, “Towards quantitative analysis of retinal features in optical coherence tomography,” Med. Eng. Phys. 29(4), 432–441 (2007).
[CrossRef]

Bashkansky, M.

Beaton, S.

H. Ishikawa, D. M. Stein, G. Wollstein, S. Beaton, J. G. Fujimoto, and J. S. Schuman, “Macular segmentation with optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 46(6), 2012–2017 (2005).
[CrossRef] [PubMed]

Bernstein, R.

R. Bernstein, “Adaptive nonlinear filters for simultaneous removal of different kinds of noise in images,” IEEE Trans. Circ. Syst. 34, 1275–1291 (1987).
[CrossRef]

Bilenca, A.

Bizheva, K.

Blair, M.

A. M. Bagci, M. Shahidi, R. Ansari, M. Blair, N. P. Blair, and R. Zelkha, “Thickness profiles of retinal layers by optical coherence tomography image segmentation,” Am. J. Ophthalmol. 146(5), 679–687 (2008).
[CrossRef] [PubMed]

Blair, N. P.

A. M. Bagci, M. Shahidi, R. Ansari, M. Blair, N. P. Blair, and R. Zelkha, “Thickness profiles of retinal layers by optical coherence tomography image segmentation,” Am. J. Ophthalmol. 146(5), 679–687 (2008).
[CrossRef] [PubMed]

Bouma, B. E.

A. Ozcan, A. Bilenca, A. E. Desjardins, B. E. Bouma, and G. J. Tearney, “Speckle reduction in optical coherence tomography images using digital filtering,” J. Opt. Soc. Am. A 24(7), 1901–1910 (2007).
[CrossRef]

N. Iftimia, B. E. Bouma, and G. J. Tearney, “Speckle reduction in optical coherence tomography by “path length encoded” angular compounding,” J. Biomed. Opt. 8(2), 260–263 (2003).
[CrossRef] [PubMed]

Brezinski, M. E.

J. Rogowska and M. E. Brezinski, “Evaluation of the adaptive speckle suppression filter for coronary optical coherence tomography imaging,” IEEE Trans. Med. Imaging 19(12), 1261–1266 (2000).
[CrossRef]

Burckhardt, C.

C. Burckhardt, “Speckle in ultrasound b-mode scans,” IEEE Trans. Sonics Ultrason. 25, 1–6 (1978).
[CrossRef]

Cabrera Fernández, D.

Chavel, P.

D. Kuan, A. Sawchuk, T. Strand, and P. Chavel, “Adaptive noise smoothing filter for images with signal-dependent noise,” IEEE Trans. Pattern Anal. Mach. Intell. 7, 165–177 (1985).
[CrossRef] [PubMed]

Christensen, U.

T. M. Jørgensen, J. Thomadsen, U. Christensen, W. Soliman, and B. Sander, “Enhancing the signal-to-noise ratio in ophthalmic optical coherence tomography by image registration--method and clinical examples,” J. Biomed. Opt. 12(4), 041208 (2007).
[CrossRef] [PubMed]

Desjardins, A. E.

Drexler, W.

W. Drexler, U. Morgner, R. K. Ghanta, F. X. Kärtner, J. S. Schuman, and J. G. Fujimoto, “Ultrahigh-resolution ophthalmic optical coherence tomography,” Nat. Med. 7(4), 502–507 (2001).
[CrossRef] [PubMed]

Fercher, A. F.

M. Pircher, E. Gotzinger, R. Leitgeb, A. F. Fercher, and C. K. Hitzenberger, “Speckle reduction in optical coherence tomography by frequency compounding,” J. Biomed. Opt. 8(3), 565–569 (2003).
[CrossRef] [PubMed]

Fernández, D. C.

H. M. Salinas and D. C. Fernández, “Comparison of PDE-based nonlinear diffusion approaches for image enhancement and denoising in optical coherence tomography,” IEEE Trans. Med. Imaging 26(6), 761–771 (2007).
[CrossRef] [PubMed]

Forsberg, F.

A. J. Healey, S. Leeman, and F. Forsberg, “Turning off speckle,” Acoust. Imaging 19, 433–437 (1992).
[CrossRef]

Fortunato, P.

M. Baroni, P. Fortunato, and A. La Torre, “Towards quantitative analysis of retinal features in optical coherence tomography,” Med. Eng. Phys. 29(4), 432–441 (2007).
[CrossRef]

Franceschetti, G.

Fried, D. L.

Fujimoto, J. G.

H. Ishikawa, D. M. Stein, G. Wollstein, S. Beaton, J. G. Fujimoto, and J. S. Schuman, “Macular segmentation with optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 46(6), 2012–2017 (2005).
[CrossRef] [PubMed]

W. Drexler, U. Morgner, R. K. Ghanta, F. X. Kärtner, J. S. Schuman, and J. G. Fujimoto, “Ultrahigh-resolution ophthalmic optical coherence tomography,” Nat. Med. 7(4), 502–507 (2001).
[CrossRef] [PubMed]

Ghanta, R. K.

W. Drexler, U. Morgner, R. K. Ghanta, F. X. Kärtner, J. S. Schuman, and J. G. Fujimoto, “Ultrahigh-resolution ophthalmic optical coherence tomography,” Nat. Med. 7(4), 502–507 (2001).
[CrossRef] [PubMed]

Gilboa, G.

G. Gilboa, N. Sochen, and Y. Y. Zeevi, “Image enhancement and denoising by complex diffusion processes,” IEEE Trans. Pattern Anal. Mach. Intell. 26(8), 1020–1036 (2004).
[CrossRef]

Goodman, J. W.

Gotzinger, E.

M. Pircher, E. Gotzinger, R. Leitgeb, A. F. Fercher, and C. K. Hitzenberger, “Speckle reduction in optical coherence tomography by frequency compounding,” J. Biomed. Opt. 8(3), 565–569 (2003).
[CrossRef] [PubMed]

Healey, A. J.

A. J. Healey, S. Leeman, and F. Forsberg, “Turning off speckle,” Acoust. Imaging 19, 433–437 (1992).
[CrossRef]

Hitzenberger, C. K.

M. Pircher, E. Gotzinger, R. Leitgeb, A. F. Fercher, and C. K. Hitzenberger, “Speckle reduction in optical coherence tomography by frequency compounding,” J. Biomed. Opt. 8(3), 565–569 (2003).
[CrossRef] [PubMed]

Hougaard, J. L.

B. Sander, M. Larsen, L. Thrane, J. L. Hougaard, and T. M. Jørgensen, “Enhanced optical coherence tomography imaging by multiple scan averaging,” Br. J. Ophthalmol. 89(2), 207–212 (2005).
[CrossRef] [PubMed]

Huang, D.

O. Tan, G. Li, A. T. H. Lu, R. Varma, D. Huang, and Advanced Imaging for Glaucoma Study Group, “Mapping of macular substructures with optical coherence tomography for glaucoma diagnosis,” Ophthalmology 115(6), 949–956 (2008).
[CrossRef]

Iftimia, N.

N. Iftimia, B. E. Bouma, and G. J. Tearney, “Speckle reduction in optical coherence tomography by “path length encoded” angular compounding,” J. Biomed. Opt. 8(2), 260–263 (2003).
[CrossRef] [PubMed]

Ishikawa, H.

H. Ishikawa, D. M. Stein, G. Wollstein, S. Beaton, J. G. Fujimoto, and J. S. Schuman, “Macular segmentation with optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 46(6), 2012–2017 (2005).
[CrossRef] [PubMed]

Jørgensen, T. M.

T. M. Jørgensen, J. Thomadsen, U. Christensen, W. Soliman, and B. Sander, “Enhancing the signal-to-noise ratio in ophthalmic optical coherence tomography by image registration--method and clinical examples,” J. Biomed. Opt. 12(4), 041208 (2007).
[CrossRef] [PubMed]

B. Sander, M. Larsen, L. Thrane, J. L. Hougaard, and T. M. Jørgensen, “Enhanced optical coherence tomography imaging by multiple scan averaging,” Br. J. Ophthalmol. 89(2), 207–212 (2005).
[CrossRef] [PubMed]

Kärtner, F. X.

W. Drexler, U. Morgner, R. K. Ghanta, F. X. Kärtner, J. S. Schuman, and J. G. Fujimoto, “Ultrahigh-resolution ophthalmic optical coherence tomography,” Nat. Med. 7(4), 502–507 (2001).
[CrossRef] [PubMed]

Kim, E.

J. Kim, D. T. Miller, E. Kim, S. Oh, J. Oh, and T. E. Milner, “Optical coherence tomography speckle reduction by a partially spatially coherent source,” J. Biomed. Opt. 10(6), 064034 (2005).
[CrossRef]

Kim, J.

J. Kim, D. T. Miller, E. Kim, S. Oh, J. Oh, and T. E. Milner, “Optical coherence tomography speckle reduction by a partially spatially coherent source,” J. Biomed. Opt. 10(6), 064034 (2005).
[CrossRef]

Kuan, D.

D. Kuan, A. Sawchuk, T. Strand, and P. Chavel, “Adaptive noise smoothing filter for images with signal-dependent noise,” IEEE Trans. Pattern Anal. Mach. Intell. 7, 165–177 (1985).
[CrossRef] [PubMed]

La Torre, A.

M. Baroni, P. Fortunato, and A. La Torre, “Towards quantitative analysis of retinal features in optical coherence tomography,” Med. Eng. Phys. 29(4), 432–441 (2007).
[CrossRef]

Larsen, M.

B. Sander, M. Larsen, L. Thrane, J. L. Hougaard, and T. M. Jørgensen, “Enhanced optical coherence tomography imaging by multiple scan averaging,” Br. J. Ophthalmol. 89(2), 207–212 (2005).
[CrossRef] [PubMed]

Lee, J.

J. Lee, “Speckle analysis and smoothing of synthetic aperture radar images,” Comput. Graph. Image Process. 17, 24–32 (1981).
[CrossRef]

Lee, S. L.

K. M. Yung, S. L. Lee, and J. M. Schmitt, “Phase-domain processing of optical coherence tomography images,” J. Biomed. Opt. 4, 125–136 (1999).
[CrossRef]

Leeman, S.

A. J. Healey, S. Leeman, and F. Forsberg, “Turning off speckle,” Acoust. Imaging 19, 433–437 (1992).
[CrossRef]

Leitgeb, R.

M. Pircher, E. Gotzinger, R. Leitgeb, A. F. Fercher, and C. K. Hitzenberger, “Speckle reduction in optical coherence tomography by frequency compounding,” J. Biomed. Opt. 8(3), 565–569 (2003).
[CrossRef] [PubMed]

Li, G.

O. Tan, G. Li, A. T. H. Lu, R. Varma, D. Huang, and Advanced Imaging for Glaucoma Study Group, “Mapping of macular substructures with optical coherence tomography for glaucoma diagnosis,” Ophthalmology 115(6), 949–956 (2008).
[CrossRef]

Lopez, H.

R. Wagner, S. Smith, J. Sandrik, and H. Lopez, “Statistics of speckle in ultrasound b-scans,” IEEE Trans. Sonics Ultrason. 30, 156–163 (1983).
[CrossRef]

Lu, A. T. H.

O. Tan, G. Li, A. T. H. Lu, R. Varma, D. Huang, and Advanced Imaging for Glaucoma Study Group, “Mapping of macular substructures with optical coherence tomography for glaucoma diagnosis,” Ophthalmology 115(6), 949–956 (2008).
[CrossRef]

Malik, J.

P. Perona and J. Malik, “Scale-space and edge detection using anisotropic diffusion,” IEEE Trans. Pattern Anal. Mach. Intell. 12, 629–639 (1990).
[CrossRef]

Miller, D. T.

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[CrossRef]

Milner, T. E.

J. Kim, D. T. Miller, E. Kim, S. Oh, J. Oh, and T. E. Milner, “Optical coherence tomography speckle reduction by a partially spatially coherent source,” J. Biomed. Opt. 10(6), 064034 (2005).
[CrossRef]

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W. Drexler, U. Morgner, R. K. Ghanta, F. X. Kärtner, J. S. Schuman, and J. G. Fujimoto, “Ultrahigh-resolution ophthalmic optical coherence tomography,” Nat. Med. 7(4), 502–507 (2001).
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J. Kim, D. T. Miller, E. Kim, S. Oh, J. Oh, and T. E. Milner, “Optical coherence tomography speckle reduction by a partially spatially coherent source,” J. Biomed. Opt. 10(6), 064034 (2005).
[CrossRef]

Oh, S.

J. Kim, D. T. Miller, E. Kim, S. Oh, J. Oh, and T. E. Milner, “Optical coherence tomography speckle reduction by a partially spatially coherent source,” J. Biomed. Opt. 10(6), 064034 (2005).
[CrossRef]

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P. Perona and J. Malik, “Scale-space and edge detection using anisotropic diffusion,” IEEE Trans. Pattern Anal. Mach. Intell. 12, 629–639 (1990).
[CrossRef]

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M. Pircher, E. Gotzinger, R. Leitgeb, A. F. Fercher, and C. K. Hitzenberger, “Speckle reduction in optical coherence tomography by frequency compounding,” J. Biomed. Opt. 8(3), 565–569 (2003).
[CrossRef] [PubMed]

Puliafito, C. A.

Puvanathasan, P.

Reintjes, J.

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J. Rogowska and M. E. Brezinski, “Evaluation of the adaptive speckle suppression filter for coronary optical coherence tomography imaging,” IEEE Trans. Med. Imaging 19(12), 1261–1266 (2000).
[CrossRef]

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H. M. Salinas and D. C. Fernández, “Comparison of PDE-based nonlinear diffusion approaches for image enhancement and denoising in optical coherence tomography,” IEEE Trans. Med. Imaging 26(6), 761–771 (2007).
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R. Wagner, S. Smith, J. Sandrik, and H. Lopez, “Statistics of speckle in ultrasound b-scans,” IEEE Trans. Sonics Ultrason. 30, 156–163 (1983).
[CrossRef]

Sawchuk, A.

D. Kuan, A. Sawchuk, T. Strand, and P. Chavel, “Adaptive noise smoothing filter for images with signal-dependent noise,” IEEE Trans. Pattern Anal. Mach. Intell. 7, 165–177 (1985).
[CrossRef] [PubMed]

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Schmitt, J. M.

K. M. Yung, S. L. Lee, and J. M. Schmitt, “Phase-domain processing of optical coherence tomography images,” J. Biomed. Opt. 4, 125–136 (1999).
[CrossRef]

J. M. Schmitt, “Restoration of optical coherence images of living tissue using the clean algorithm,” J. Biomed. Opt. 3, 66–75 (1998).
[CrossRef]

S. H. Xiang, L. Zhou, and J. M. Schmitt, “Speckle noise reduction for optical coherence tomography,” Proc. SPIE 3196, 79–88 (1998).
[CrossRef]

J. M. Schmitt, “Array detection for speckle reduction in optical coherence microscopy,” Phys. Med. Biol. 42(7), 1427–1439 (1997).
[CrossRef] [PubMed]

Schuman, J. S.

H. Ishikawa, D. M. Stein, G. Wollstein, S. Beaton, J. G. Fujimoto, and J. S. Schuman, “Macular segmentation with optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 46(6), 2012–2017 (2005).
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[CrossRef] [PubMed]

Shahidi, M.

A. M. Bagci, M. Shahidi, R. Ansari, M. Blair, N. P. Blair, and R. Zelkha, “Thickness profiles of retinal layers by optical coherence tomography image segmentation,” Am. J. Ophthalmol. 146(5), 679–687 (2008).
[CrossRef] [PubMed]

M. Shahidi, Z. Wang, and R. Zelkha, “Quantitative thickness measurement of retinal layers imaged by optical coherence tomography,” Am. J. Ophthalmol. 139(6), 1056–1061 (2005).
[CrossRef] [PubMed]

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P. Shankar and V. Newhouse, “Speckle reduction with improved resolution in ultrasound images,” IEEE Trans. Sonics Ultrason. SU-32, 537–543 (1985).

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R. Wagner, S. Smith, J. Sandrik, and H. Lopez, “Statistics of speckle in ultrasound b-scans,” IEEE Trans. Sonics Ultrason. 30, 156–163 (1983).
[CrossRef]

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G. Gilboa, N. Sochen, and Y. Y. Zeevi, “Image enhancement and denoising by complex diffusion processes,” IEEE Trans. Pattern Anal. Mach. Intell. 26(8), 1020–1036 (2004).
[CrossRef]

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T. M. Jørgensen, J. Thomadsen, U. Christensen, W. Soliman, and B. Sander, “Enhancing the signal-to-noise ratio in ophthalmic optical coherence tomography by image registration--method and clinical examples,” J. Biomed. Opt. 12(4), 041208 (2007).
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H. Ishikawa, D. M. Stein, G. Wollstein, S. Beaton, J. G. Fujimoto, and J. S. Schuman, “Macular segmentation with optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 46(6), 2012–2017 (2005).
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D. Kuan, A. Sawchuk, T. Strand, and P. Chavel, “Adaptive noise smoothing filter for images with signal-dependent noise,” IEEE Trans. Pattern Anal. Mach. Intell. 7, 165–177 (1985).
[CrossRef] [PubMed]

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T. M. Jørgensen, J. Thomadsen, U. Christensen, W. Soliman, and B. Sander, “Enhancing the signal-to-noise ratio in ophthalmic optical coherence tomography by image registration--method and clinical examples,” J. Biomed. Opt. 12(4), 041208 (2007).
[CrossRef] [PubMed]

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B. Sander, M. Larsen, L. Thrane, J. L. Hougaard, and T. M. Jørgensen, “Enhanced optical coherence tomography imaging by multiple scan averaging,” Br. J. Ophthalmol. 89(2), 207–212 (2005).
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J. G. Abbott and F. L. Thurstone, “Acoustic speckle: theory and experimental analysis,” Ultrason. Imaging 1(4), 303–324 (1979).
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O. Tan, G. Li, A. T. H. Lu, R. Varma, D. Huang, and Advanced Imaging for Glaucoma Study Group, “Mapping of macular substructures with optical coherence tomography for glaucoma diagnosis,” Ophthalmology 115(6), 949–956 (2008).
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R. Wagner, S. Smith, J. Sandrik, and H. Lopez, “Statistics of speckle in ultrasound b-scans,” IEEE Trans. Sonics Ultrason. 30, 156–163 (1983).
[CrossRef]

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M. Shahidi, Z. Wang, and R. Zelkha, “Quantitative thickness measurement of retinal layers imaged by optical coherence tomography,” Am. J. Ophthalmol. 139(6), 1056–1061 (2005).
[CrossRef] [PubMed]

Wollstein, G.

H. Ishikawa, D. M. Stein, G. Wollstein, S. Beaton, J. G. Fujimoto, and J. S. Schuman, “Macular segmentation with optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 46(6), 2012–2017 (2005).
[CrossRef] [PubMed]

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S. H. Xiang, L. Zhou, and J. M. Schmitt, “Speckle noise reduction for optical coherence tomography,” Proc. SPIE 3196, 79–88 (1998).
[CrossRef]

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K. M. Yung, S. L. Lee, and J. M. Schmitt, “Phase-domain processing of optical coherence tomography images,” J. Biomed. Opt. 4, 125–136 (1999).
[CrossRef]

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G. Gilboa, N. Sochen, and Y. Y. Zeevi, “Image enhancement and denoising by complex diffusion processes,” IEEE Trans. Pattern Anal. Mach. Intell. 26(8), 1020–1036 (2004).
[CrossRef]

Zelkha, R.

A. M. Bagci, M. Shahidi, R. Ansari, M. Blair, N. P. Blair, and R. Zelkha, “Thickness profiles of retinal layers by optical coherence tomography image segmentation,” Am. J. Ophthalmol. 146(5), 679–687 (2008).
[CrossRef] [PubMed]

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[CrossRef] [PubMed]

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S. H. Xiang, L. Zhou, and J. M. Schmitt, “Speckle noise reduction for optical coherence tomography,” Proc. SPIE 3196, 79–88 (1998).
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M. Shahidi, Z. Wang, and R. Zelkha, “Quantitative thickness measurement of retinal layers imaged by optical coherence tomography,” Am. J. Ophthalmol. 139(6), 1056–1061 (2005).
[CrossRef] [PubMed]

A. M. Bagci, M. Shahidi, R. Ansari, M. Blair, N. P. Blair, and R. Zelkha, “Thickness profiles of retinal layers by optical coherence tomography image segmentation,” Am. J. Ophthalmol. 146(5), 679–687 (2008).
[CrossRef] [PubMed]

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B. Sander, M. Larsen, L. Thrane, J. L. Hougaard, and T. M. Jørgensen, “Enhanced optical coherence tomography imaging by multiple scan averaging,” Br. J. Ophthalmol. 89(2), 207–212 (2005).
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R. Bernstein, “Adaptive nonlinear filters for simultaneous removal of different kinds of noise in images,” IEEE Trans. Circ. Syst. 34, 1275–1291 (1987).
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IEEE Trans. Med. Imaging (2)

H. M. Salinas and D. C. Fernández, “Comparison of PDE-based nonlinear diffusion approaches for image enhancement and denoising in optical coherence tomography,” IEEE Trans. Med. Imaging 26(6), 761–771 (2007).
[CrossRef] [PubMed]

J. Rogowska and M. E. Brezinski, “Evaluation of the adaptive speckle suppression filter for coronary optical coherence tomography imaging,” IEEE Trans. Med. Imaging 19(12), 1261–1266 (2000).
[CrossRef]

IEEE Trans. Pattern Anal. Mach. Intell. (3)

P. Perona and J. Malik, “Scale-space and edge detection using anisotropic diffusion,” IEEE Trans. Pattern Anal. Mach. Intell. 12, 629–639 (1990).
[CrossRef]

D. Kuan, A. Sawchuk, T. Strand, and P. Chavel, “Adaptive noise smoothing filter for images with signal-dependent noise,” IEEE Trans. Pattern Anal. Mach. Intell. 7, 165–177 (1985).
[CrossRef] [PubMed]

G. Gilboa, N. Sochen, and Y. Y. Zeevi, “Image enhancement and denoising by complex diffusion processes,” IEEE Trans. Pattern Anal. Mach. Intell. 26(8), 1020–1036 (2004).
[CrossRef]

IEEE Trans. Sonics Ultrason. (3)

P. Shankar and V. Newhouse, “Speckle reduction with improved resolution in ultrasound images,” IEEE Trans. Sonics Ultrason. SU-32, 537–543 (1985).

R. Wagner, S. Smith, J. Sandrik, and H. Lopez, “Statistics of speckle in ultrasound b-scans,” IEEE Trans. Sonics Ultrason. 30, 156–163 (1983).
[CrossRef]

C. Burckhardt, “Speckle in ultrasound b-mode scans,” IEEE Trans. Sonics Ultrason. 25, 1–6 (1978).
[CrossRef]

Invest. Ophthalmol. Vis. Sci. (1)

H. Ishikawa, D. M. Stein, G. Wollstein, S. Beaton, J. G. Fujimoto, and J. S. Schuman, “Macular segmentation with optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 46(6), 2012–2017 (2005).
[CrossRef] [PubMed]

J. Biomed. Opt. (6)

M. Pircher, E. Gotzinger, R. Leitgeb, A. F. Fercher, and C. K. Hitzenberger, “Speckle reduction in optical coherence tomography by frequency compounding,” J. Biomed. Opt. 8(3), 565–569 (2003).
[CrossRef] [PubMed]

J. Kim, D. T. Miller, E. Kim, S. Oh, J. Oh, and T. E. Milner, “Optical coherence tomography speckle reduction by a partially spatially coherent source,” J. Biomed. Opt. 10(6), 064034 (2005).
[CrossRef]

K. M. Yung, S. L. Lee, and J. M. Schmitt, “Phase-domain processing of optical coherence tomography images,” J. Biomed. Opt. 4, 125–136 (1999).
[CrossRef]

T. M. Jørgensen, J. Thomadsen, U. Christensen, W. Soliman, and B. Sander, “Enhancing the signal-to-noise ratio in ophthalmic optical coherence tomography by image registration--method and clinical examples,” J. Biomed. Opt. 12(4), 041208 (2007).
[CrossRef] [PubMed]

N. Iftimia, B. E. Bouma, and G. J. Tearney, “Speckle reduction in optical coherence tomography by “path length encoded” angular compounding,” J. Biomed. Opt. 8(2), 260–263 (2003).
[CrossRef] [PubMed]

J. M. Schmitt, “Restoration of optical coherence images of living tissue using the clean algorithm,” J. Biomed. Opt. 3, 66–75 (1998).
[CrossRef]

J. Opt. Soc. Am. (1)

J. Opt. Soc. Am. A (3)

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M. Baroni, P. Fortunato, and A. La Torre, “Towards quantitative analysis of retinal features in optical coherence tomography,” Med. Eng. Phys. 29(4), 432–441 (2007).
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Nat. Med. (1)

W. Drexler, U. Morgner, R. K. Ghanta, F. X. Kärtner, J. S. Schuman, and J. G. Fujimoto, “Ultrahigh-resolution ophthalmic optical coherence tomography,” Nat. Med. 7(4), 502–507 (2001).
[CrossRef] [PubMed]

Ophthalmology (1)

O. Tan, G. Li, A. T. H. Lu, R. Varma, D. Huang, and Advanced Imaging for Glaucoma Study Group, “Mapping of macular substructures with optical coherence tomography for glaucoma diagnosis,” Ophthalmology 115(6), 949–956 (2008).
[CrossRef]

Opt. Express (2)

Opt. Lett. (1)

Phys. Med. Biol. (1)

J. M. Schmitt, “Array detection for speckle reduction in optical coherence microscopy,” Phys. Med. Biol. 42(7), 1427–1439 (1997).
[CrossRef] [PubMed]

Proc. SPIE (1)

S. H. Xiang, L. Zhou, and J. M. Schmitt, “Speckle noise reduction for optical coherence tomography,” Proc. SPIE 3196, 79–88 (1998).
[CrossRef]

Ultrason. Imaging (1)

J. G. Abbott and F. L. Thurstone, “Acoustic speckle: theory and experimental analysis,” Ultrason. Imaging 1(4), 303–324 (1979).
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Other (6)

A. F. Fercher, Optical Coherence Tomography: Technology and Applications (Springer, New York, 2008), chap. 4.

D. Koozekanani, K. Boyer, and C. Roberts, “Retinal thickness measurements in optical coherence tomography using a Markov boundary model”, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (Hilton Head, SC, 2000), pp. 2363–2370.

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Matlab (Matlab – The MathWorks Inc., Natick, MA, USA). http://www.mathworks.com .

K. Abd-Elmoniem, “Feedback coherent anisotropic diffusion for high resolution image enhancement”, in Proceedings of IEEE International Symposium on Biomedical Imaging, (Washington, DC, 2002), pp. 693–696.

A. Araújo, S. Barbeiro and P. Serranho, “Stability of finite difference schemes for complex diffusion processes”, DMUC report 10–23, (2010).

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Figures (7)

Fig. 1
Fig. 1

Optical coherence tomography (OCT). Left: volumetric OCT data shown over an eye fundus reference. Right: example of a B-scan (top) and an A-scan profile (bottom).

Fig. 2
Fig. 2

Family of curves from the diffusion coefficient as a function of κ (Eq. (7).

Fig. 3
Fig. 3

Typical evolution of the step in time (Δt) for the proposed adaptive process.

Fig. 4
Fig. 4

Synthetic image (left) and the noisy versions: Matlab speckle “imnoise” (center), and the Hadamard product of two gaussian functions (right). The dashed regions in the left image define the areas of low- and high-intensity regions used to compute performance metrics.

Fig. 5
Fig. 5

Filtered images using the traditional NCDF (left) and the modified NCDF (right) for the “imnoise” (top) and “randn.randn” (bottom) noise sources.

Fig. 6
Fig. 6

Profile comparison between the original (left image from Fig. 4), noisy (right image from Fig. 4), traditional (bottom-left from Fig. 5) and improved (bottom-right from Fig. 5) filtered NCDF, respectively solid black, dashed blue, solid green and solid red lines. All these profiles were taken horizontally from the bottom-left part of the respective images to demonstrate the filter performance on step and ramp edges.

Fig. 7
Fig. 7

A high-definition B-scan (top-left). Color-coded inset from the dashed area on the left (top right). Filter results for the traditional NCDF (bottom-left) and the proposed NCDF (bottom right). All color-coded figures use the same color map and color limits for easy comparison. Note the well-defined interface between the tissue and the vitreous regions.

Tables (1)

Tables Icon

Table 1 Performance metrics computed from 50 runs (mean ± SD). LI = low-intensity areas; HI = high-intensity areas; MSE = mean square error; ENL = effective number of looks; CNR = contrast to noise ratio.

Equations (14)

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

I t = ( D I ) ,
I i , j , m ( n + 1 ) = I i , j , m ( n ) + Δ t ( n ) ( D ¯ i , j , m ( n ) Δ h I i , j , m ( n ) + h D i , j , m ( n ) h I i , j , m ( n ) ) ,
D ¯ i , j ( n ) = 4 D i , j ( n ) + D i ± 1 , j ( n ) + D i , j ± 1 ( n ) 8 ,
D ¯ i , j , m ( n ) = 6 D i , j , m ( n ) + D i ± 1 , j , m ( n ) + D i , j ± 1 , m ( n ) + D i , j , m ± 1 ( n ) 12 .
Δ t ( n ) 1 α max i , j , m [ Re ( D i , j , m ( n ) ) + | Im ( D i , j , m ( n ) ) | ] ,
D = exp ( i θ ) 1 + ( Im ( I ) κ θ ) 2 ,
D 1 1 + ( Δ I k ) 2 .
L ( x ) = 2 A w π ( w 2 + 4 ( x x c ) 2 ) .
κ = κ M A X + ( κ M I N κ M A X ) g min ( g ) max ( g ) min ( g ) ,
g = G N , σ Re ( I ) ,
Δ t ( n ) = 1 α [ a + b exp { max ( | Re ( I ( n ) t ) | / Re ( I ( n ) ) ) } ] ,
M S E = 1 M P i j | I ( i , j ) I f ( i , j ) | 2 .
E N L = μ H 2 σ H 2 .
C N R = μ R μ H σ R 2 + σ H 2 .

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