3 Speckle Noise Reduction and Enhancement for OCT Images
69
30. G. Peyré, Advanced Signal, Image and Surface Processing (University Paris-Dauphine, Ceremade, 2010)
31. S.J. Wright, R.D. Nowak, M.A. Figueiredo, Sparse reconstruction by separable approximation. IEEE Trans. Signal Process. 57, 2479–2493 (2009)
32. H. Rabbani, R. Nezafat, S. Gazor, Wavelet-domain medical image denoising using bivariate
Laplacian mixture model. IEEE Trans. Biomed. Eng. 56, 2826–2837 (2009)
33. R.R. Coifman, M. Maggioni, Diffusion wavelets. Appl. Comput. Harmonic Anal. 21, 53–94
(2006)
34. D. Cabrera Fernández, N. Villate, C. Puliafito, P. Rosenfeld, Comparing total macular volume
changes measured by optical coherence tomography with retinal lesion volume estimated by
active contours. Invest. Ophtalmol. Vis. Sci. 45, 3072 (2004)
35. G. Gregori, R. Knighton, A robust algorithm for retinal thickness measurements using optical
coherence tomography (Stratus OCT). Invest. Ophtalmol. Vis. Sci. 45, 3007 (2004)
36. J. Rogowska, M.E. Brezinski, Evaluation of the adaptive speckle suppression filter for coronary optical coherence tomography imaging. IEEE Trans. Med. Imaging 19, 1261–1266
(2000)
37. A.M. Bagci, M. Shahidi, R. Ansari, M. Blair, N.P. Blair, R. Zelkha, Thickness profiles of
retinal layers by optical coherence tomography image segmentation. Am. J. Ophthalmol.
146, 679–687 (2008). (e1)
38. R. Bernardes, C. Maduro, P. Serranho, A. Araújo, S. Barbeiro, J. Cunha-Vaz, Improved adaptive complex diffusion despeckling filter. Opt. Express 18, 24048–24059 (2010)
39. A.R. Fuller, R.J. Zawadzki, S. Choi, D.F. Wiley, J.S. Werner, B. Hamann, Segmentation of
three-dimensional retinal image data. IEEE Trans. Visual Comput. Graphics 13, 1719–1726
(2007)
40. A. Mishra, A. Wong, K. Bizheva, D.A. Clausi, Intra-retinal layer segmentation in optical
coherence tomography images. Opt. Express 17, 23719–23728 (2009)
41. F. Luan, Y. Wu, Application of RPCA in optical coherence tomography for speckle noise
reduction. Laser Phys. Lett. 10, 035603 (2013)
42. V. Gupta, C.C. Chan, C.-L. Poh, T.H. Chow, T.C. Meng, N.B. Koon, Computerized automation of wavelet based denoising method to reduce speckle noise in OCT images, in International Conference on Information Technology and Applications in Biomedicine, ITAB (2008),
pp. 120–123
43. M.A. Mayer, A. Borsdorf, M. Wagner, J. Hornegger, C.Y. Mardin, R.P. Tornow, Wavelet
denoising of multiframe optical coherence tomography data. Biomed. Opt. Express 3, 572–589
(2012)
44. Z. Jian, Z. Yu, L. Yu, B. Rao, Z. Chen, B.J. Tromberg, Speckle attenuation in optical coherence
tomography by curvelet shrinkage. Opt. Lett. 34, 1516–1518 (2009)
45. S. Chitchian, M.A. Fiddy, N.M. Fried, Denoising during optical coherence tomography of the
prostate nerves via wavelet shrinkage using dual-tree complex wavelet transform. J. Biomed.
Opt.cs 14, 014031–014031-6 (2009)
46. V. Kaji´ c, M. Esmaeelpour, B. Považay, D. Marshall, P.L. Rosin, W. Drexler, Automated
choroidal segmentation of 1060 nm OCT in healthy and pathologic eyes using a statistical
model. Biomed. Opt. Express 3, 86–103 (2012)
47. V. Kaji´ c, B. Považay, B. Hermann, B. Hofer, D. Marshall, P.L. Rosin et al., Robust segmentation of intraretinal layers in the normal human fovea using a novel statistical model based
on texture and shape analysis. Opt. Express 18, 14730–14744 (2010)
48. R. Kafieh, H. Rabbani, M.D. Abramoff, M. Sonka, Curvature correction of retinal OCTs using
graph-based geometry detection. Phys. Med. Biol. 58, 2925 (2013)
49. Z. Amini, H. Rabbani, Statistical modeling of retinal optical coherence tomography. IEEE
Trans. Med. Imaging 35, 1544–1554 (2016)
50. A. Achim, A. Bezerianos, P. Tsakalides, Novel Bayesian multiscale method for speckle
removal in medical ultrasound images. IEEE Trans. Med. Imaging 20, 772–783 (2001)
51. A. Pizurica, L. Jovanov, B. Huysmans, V. Zlokolica, P. De Keyser, F. Dhaenens et al., Multiresolution denoising for optical coherence tomography: a review and evaluation. Curr. Med.
Imaging Rev. 4, 270–284 (2008)
69
30. G. Peyré, Advanced Signal, Image and Surface Processing (University Paris-Dauphine, Ceremade, 2010)
31. S.J. Wright, R.D. Nowak, M.A. Figueiredo, Sparse reconstruction by separable approximation. IEEE Trans. Signal Process. 57, 2479–2493 (2009)
32. H. Rabbani, R. Nezafat, S. Gazor, Wavelet-domain medical image denoising using bivariate
Laplacian mixture model. IEEE Trans. Biomed. Eng. 56, 2826–2837 (2009)
33. R.R. Coifman, M. Maggioni, Diffusion wavelets. Appl. Comput. Harmonic Anal. 21, 53–94
(2006)
34. D. Cabrera Fernández, N. Villate, C. Puliafito, P. Rosenfeld, Comparing total macular volume
changes measured by optical coherence tomography with retinal lesion volume estimated by
active contours. Invest. Ophtalmol. Vis. Sci. 45, 3072 (2004)
35. G. Gregori, R. Knighton, A robust algorithm for retinal thickness measurements using optical
coherence tomography (Stratus OCT). Invest. Ophtalmol. Vis. Sci. 45, 3007 (2004)
36. J. Rogowska, M.E. Brezinski, Evaluation of the adaptive speckle suppression filter for coronary optical coherence tomography imaging. IEEE Trans. Med. Imaging 19, 1261–1266
(2000)
37. A.M. Bagci, M. Shahidi, R. Ansari, M. Blair, N.P. Blair, R. Zelkha, Thickness profiles of
retinal layers by optical coherence tomography image segmentation. Am. J. Ophthalmol.
146, 679–687 (2008). (e1)
38. R. Bernardes, C. Maduro, P. Serranho, A. Araújo, S. Barbeiro, J. Cunha-Vaz, Improved adaptive complex diffusion despeckling filter. Opt. Express 18, 24048–24059 (2010)
39. A.R. Fuller, R.J. Zawadzki, S. Choi, D.F. Wiley, J.S. Werner, B. Hamann, Segmentation of
three-dimensional retinal image data. IEEE Trans. Visual Comput. Graphics 13, 1719–1726
(2007)
40. A. Mishra, A. Wong, K. Bizheva, D.A. Clausi, Intra-retinal layer segmentation in optical
coherence tomography images. Opt. Express 17, 23719–23728 (2009)
41. F. Luan, Y. Wu, Application of RPCA in optical coherence tomography for speckle noise
reduction. Laser Phys. Lett. 10, 035603 (2013)
42. V. Gupta, C.C. Chan, C.-L. Poh, T.H. Chow, T.C. Meng, N.B. Koon, Computerized automation of wavelet based denoising method to reduce speckle noise in OCT images, in International Conference on Information Technology and Applications in Biomedicine, ITAB (2008),
pp. 120–123
43. M.A. Mayer, A. Borsdorf, M. Wagner, J. Hornegger, C.Y. Mardin, R.P. Tornow, Wavelet
denoising of multiframe optical coherence tomography data. Biomed. Opt. Express 3, 572–589
(2012)
44. Z. Jian, Z. Yu, L. Yu, B. Rao, Z. Chen, B.J. Tromberg, Speckle attenuation in optical coherence
tomography by curvelet shrinkage. Opt. Lett. 34, 1516–1518 (2009)
45. S. Chitchian, M.A. Fiddy, N.M. Fried, Denoising during optical coherence tomography of the
prostate nerves via wavelet shrinkage using dual-tree complex wavelet transform. J. Biomed.
Opt.cs 14, 014031–014031-6 (2009)
46. V. Kaji´ c, M. Esmaeelpour, B. Považay, D. Marshall, P.L. Rosin, W. Drexler, Automated
choroidal segmentation of 1060 nm OCT in healthy and pathologic eyes using a statistical
model. Biomed. Opt. Express 3, 86–103 (2012)
47. V. Kaji´ c, B. Považay, B. Hermann, B. Hofer, D. Marshall, P.L. Rosin et al., Robust segmentation of intraretinal layers in the normal human fovea using a novel statistical model based
on texture and shape analysis. Opt. Express 18, 14730–14744 (2010)
48. R. Kafieh, H. Rabbani, M.D. Abramoff, M. Sonka, Curvature correction of retinal OCTs using
graph-based geometry detection. Phys. Med. Biol. 58, 2925 (2013)
49. Z. Amini, H. Rabbani, Statistical modeling of retinal optical coherence tomography. IEEE
Trans. Med. Imaging 35, 1544–1554 (2016)
50. A. Achim, A. Bezerianos, P. Tsakalides, Novel Bayesian multiscale method for speckle
removal in medical ultrasound images. IEEE Trans. Med. Imaging 20, 772–783 (2001)
51. A. Pizurica, L. Jovanov, B. Huysmans, V. Zlokolica, P. De Keyser, F. Dhaenens et al., Multiresolution denoising for optical coherence tomography: a review and evaluation. Curr. Med.
Imaging Rev. 4, 270–284 (2008)