Abstract

Speckle decorrelation analysis of optical coherence tomography (OCT) signal has been used in motion tracking. In our previous study, we demonstrated that cross-correlation coefficient (XCC) between Ascans had an explicit functional dependency on the magnitude of lateral displacement (δx). In this study, we evaluated the sensitivity of speckle motion tracking using the derivative of function XCC(δx) on variable δx. We demonstrated the magnitude of the derivative can be maximized. In other words, the sensitivity of OCT speckle tracking can be optimized by using signals with appropriate amount of decorrelation for XCC calculation. Based on this finding, we developed an adaptive speckle decorrelation analysis strategy to achieve motion tracking with optimized sensitivity. Briefly, we used subsequently acquired Ascans and Ascans obtained with larger time intervals to obtain multiple values of XCC and chose the XCC value that maximized motion tracking sensitivity for displacement calculation. Instantaneous motion speed can be calculated by dividing the obtained displacement with time interval between Ascans involved in XCC calculation. We implemented the above-described algorithm in real-time using graphic processing unit (GPU) and demonstrated its effectiveness in reconstructing distortion-free OCT images using data obtained from a manually scanned OCT probe. The adaptive speckle tracking method was validated in manually scanned OCT imaging, on phantom as well as in vivo skin tissue.

© 2015 Optical Society of America

Full Article  |  PDF Article
OSA Recommended Articles
Quantitative transverse flow measurement using optical coherence tomography speckle decorrelation analysis

Xuan Liu, Yong Huang, Jessica C. Ramella-Roman, Scott A. Mathews, and Jin U. Kang
Opt. Lett. 38(5) 805-807 (2013)

Distortion-free freehand-scanning OCT implemented with real-time scanning speed variance correction

Xuan Liu, Yong Huang, and Jin U. Kang
Opt. Express 20(15) 16567-16583 (2012)

Temporally and spatially adaptive Doppler analysis for robust handheld optical coherence elastography

Xuan Liu, Farzana R. Zaki, Haokun Wu, Chizhong Wang, and Yahui Wang
Biomed. Opt. Express 9(7) 3335-3353 (2018)

References

  • View by:
  • |
  • |
  • |

  1. J. S. Lee, “Speckle analysis and smoothing of synthetic aperture radar images,” Comput. Graph. Image Process. 17(1), 24–32 (1981).
    [Crossref]
  2. R. F. Wagner, S. W. Smith, J. M. Sandrik, and H. Lopez, “Statistics of speckle in ultrasound B-scans,” IEEE Trans. Sonics Ultrason. 30(3), 156–163 (1983).
    [Crossref]
  3. J. M. Schmitt, S. H. Xiang, and K. M. Yung, “Speckle in optical coherence tomography,” J. Biomed. Opt. 4(1), 95–105 (1999).
    [Crossref] [PubMed]
  4. D. C. Adler, T. H. Ko, and J. G. Fujimoto, “Speckle reduction in optical coherence tomography images by use of a spatially adaptive wavelet filter,” Opt. Lett. 29(24), 2878–2880 (2004).
    [Crossref] [PubMed]
  5. D. L. Marks, T. S. Ralston, and S. A. Boppart, “Speckle reduction by I-divergence regularization in optical coherence tomography,” J. Opt. Soc. Am. A 22(11), 2366–2371 (2005).
    [Crossref] [PubMed]
  6. M. Pircher, E. Götzinger, 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]
  7. B. F. Kennedy, T. R. Hillman, A. Curatolo, and D. D. Sampson, “Speckle reduction in optical coherence tomography by strain compounding,” Opt. Lett. 35(14), 2445–2447 (2010).
    [Crossref] [PubMed]
  8. A. E. Desjardins, B. J. Vakoc, W. Y. Oh, S. M. Motaghiannezam, G. J. Tearney, and B. E. Bouma, “Angle-resolved optical coherence tomography with sequential angular selectivity for speckle reduction,” Opt. Express 15(10), 6200–6209 (2007).
    [Crossref] [PubMed]
  9. 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] [PubMed]
  10. Z. Jian, L. Yu, B. Rao, B. J. Tromberg, and Z. Chen, “Three-dimensional speckle suppression in Optical Coherence Tomography based on the curvelet transform,” Opt. Express 18(2), 1024–1032 (2010).
    [Crossref] [PubMed]
  11. K. W. Gossage, T. S. Tkaczyk, J. J. Rodriguez, and J. K. Barton, “Texture analysis of optical coherence tomography images: feasibility for tissue classification,” J. Biomed. Opt. 8(3), 570–575 (2003).
    [Crossref] [PubMed]
  12. K. W. Gossage, C. M. Smith, E. M. Kanter, L. P. Hariri, A. L. Stone, J. J. Rodriguez, S. K. Williams, and J. K. Barton, “Texture analysis of speckle in optical coherence tomography images of tissue phantoms,” Phys. Med. Biol. 51(6), 1563–1575 (2006).
    [Crossref] [PubMed]
  13. D. K. Kasaragod, Z. Lu, L. E. Smith, and S. J. Matcher, “Speckle texture analysis of optical coherence tomography images,” Proc. SPIE 7387, 73871V (2010).
    [Crossref]
  14. K. Kurokawa, S. Makita, Y. J. Hong, and Y. Yasuno, “Two-dimensional micro-displacement measurement for laser coagulation using optical coherence tomography,” Biomed. Opt. Express 6(1), 170–190 (2015).
    [Crossref] [PubMed]
  15. K. Kurokawa, S. Makita, Y. J. Hong, and Y. Yasuno, “In-plane and out-of-plane tissue micro-displacement measurement by correlation coefficients of optical coherence tomography,” Opt. Lett. 40(9), 2153–2156 (2015).
    [Crossref] [PubMed]
  16. A. Mariampillai, B. A. Standish, E. H. Moriyama, M. Khurana, N. R. Munce, M. K. K. Leung, J. Jiang, A. Cable, B. C. Wilson, I. A. Vitkin, and V. X. D. Yang, “Speckle variance detection of microvasculature using swept-source optical coherence tomography,” Opt. Lett. 33(13), 1530–1532 (2008).
    [Crossref] [PubMed]
  17. A. Mariampillai, M. K. K. Leung, M. Jarvi, B. A. Standish, K. Lee, B. C. Wilson, A. Vitkin, and V. X. D. Yang, “Optimized speckle variance OCT imaging of microvasculature,” Opt. Lett. 35(8), 1257–1259 (2010).
    [Crossref] [PubMed]
  18. Y. Wang and R. Wang, “Autocorrelation optical coherence tomography for mapping transverse particle-flow velocity,” Opt. Lett. 35(21), 3538–3540 (2010).
    [Crossref] [PubMed]
  19. X. Liu, K. Zhang, Y. Huang, and J. U. Kang, “Spectroscopic-speckle variance OCT for microvasculature detection and analysis,” Biomed. Opt. Express 2(11), 2995–3009 (2011).
    [Crossref] [PubMed]
  20. D. W. Cadotte, A. Mariampillai, A. Cadotte, K. K. C. Lee, T. R. Kiehl, B. C. Wilson, M. G. Fehlings, and V. X. D. Yang, “Speckle variance optical coherence tomography of the rodent spinal cord: in vivo feasibility,” Biomed. Opt. Express 3(5), 911–919 (2012).
    [Crossref] [PubMed]
  21. R. Motaghiannezam and S. Fraser, “Logarithmic intensity and speckle-based motion contrast methods for human retinal vasculature visualization using swept source optical coherence tomography,” Biomed. Opt. Express 3(3), 503–521 (2012).
    [Crossref] [PubMed]
  22. X. Liu, Y. Huang, J. C. Ramella-Roman, S. A. Mathews, and J. U. Kang, “Quantitative transverse flow measurement using optical coherence tomography speckle decorrelation analysis,” Opt. Lett. 38(5), 805–807 (2013).
    [Crossref] [PubMed]
  23. X. Liu, M. Kirby, and F. Zhao, “Motion analysis and removal in intensity variation based OCT angiography,” Biomed. Opt. Express 5(11), 3833–3847 (2014).
    [Crossref] [PubMed]
  24. A. Ahmad, S. G. Adie, E. J. Chaney, U. Sharma, and S. A. Boppart, “Cross-correlation-based image acquisition technique for manually-scanned optical coherence tomography,” Opt. Express 17(10), 8125–8136 (2009).
    [Crossref] [PubMed]
  25. X. Liu, Y. Huang, and J. U. Kang, “Distortion-free freehandscanning OCT implemented with real-time scanning speed variance correction,” Opt. Express 20(15), 16567–16583 (2012).
    [Crossref]
  26. J. G. Webster, Medical Instrumentation Application and Design (Wiley 2010).
  27. R. Leitgeb, C. Hitzenberger, and A. Fercher, “Performance of fourier domain vs. time domain optical coherence tomography,” Opt. Express 11(8), 889–894 (2003).
    [Crossref] [PubMed]
  28. J. W. Goodman, Statistical Optics (Wiley, 1985).
  29. J. W. Goodman, “Some fundamental properties of speckle,” J. Opt. Soc. Am. 66(11), 1145–1150 (1976).
    [Crossref]
  30. N. Uribe-Patarroyo, M. Villiger, and B. E. Bouma, “Quantitative technique for robust and noise-tolerant speed measurements based on speckle decorrelation in optical coherence tomography,” Opt. Express 22(20), 24411–24429 (2014).
    [Crossref] [PubMed]

2015 (2)

2014 (2)

2013 (1)

2012 (3)

2011 (1)

2010 (5)

2009 (1)

2008 (1)

2007 (2)

2006 (1)

K. W. Gossage, C. M. Smith, E. M. Kanter, L. P. Hariri, A. L. Stone, J. J. Rodriguez, S. K. Williams, and J. K. Barton, “Texture analysis of speckle in optical coherence tomography images of tissue phantoms,” Phys. Med. Biol. 51(6), 1563–1575 (2006).
[Crossref] [PubMed]

2005 (1)

2004 (1)

2003 (3)

M. Pircher, E. Götzinger, 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]

K. W. Gossage, T. S. Tkaczyk, J. J. Rodriguez, and J. K. Barton, “Texture analysis of optical coherence tomography images: feasibility for tissue classification,” J. Biomed. Opt. 8(3), 570–575 (2003).
[Crossref] [PubMed]

R. Leitgeb, C. Hitzenberger, and A. Fercher, “Performance of fourier domain vs. time domain optical coherence tomography,” Opt. Express 11(8), 889–894 (2003).
[Crossref] [PubMed]

1999 (1)

J. M. Schmitt, S. H. Xiang, and K. M. Yung, “Speckle in optical coherence tomography,” J. Biomed. Opt. 4(1), 95–105 (1999).
[Crossref] [PubMed]

1983 (1)

R. F. Wagner, S. W. Smith, J. M. Sandrik, and H. Lopez, “Statistics of speckle in ultrasound B-scans,” IEEE Trans. Sonics Ultrason. 30(3), 156–163 (1983).
[Crossref]

1981 (1)

J. S. Lee, “Speckle analysis and smoothing of synthetic aperture radar images,” Comput. Graph. Image Process. 17(1), 24–32 (1981).
[Crossref]

1976 (1)

Adie, S. G.

Adler, D. C.

Ahmad, A.

Barton, J. K.

K. W. Gossage, C. M. Smith, E. M. Kanter, L. P. Hariri, A. L. Stone, J. J. Rodriguez, S. K. Williams, and J. K. Barton, “Texture analysis of speckle in optical coherence tomography images of tissue phantoms,” Phys. Med. Biol. 51(6), 1563–1575 (2006).
[Crossref] [PubMed]

K. W. Gossage, T. S. Tkaczyk, J. J. Rodriguez, and J. K. Barton, “Texture analysis of optical coherence tomography images: feasibility for tissue classification,” J. Biomed. Opt. 8(3), 570–575 (2003).
[Crossref] [PubMed]

Bilenca, A.

Boppart, S. A.

Bouma, B. E.

Cable, A.

Cadotte, A.

Cadotte, D. W.

Chaney, E. J.

Chen, Z.

Curatolo, A.

Desjardins, A. E.

Fehlings, M. G.

Fercher, A.

Fercher, A. F.

M. Pircher, E. Götzinger, 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]

Fraser, S.

Fujimoto, J. G.

Goodman, J. W.

Gossage, K. W.

K. W. Gossage, C. M. Smith, E. M. Kanter, L. P. Hariri, A. L. Stone, J. J. Rodriguez, S. K. Williams, and J. K. Barton, “Texture analysis of speckle in optical coherence tomography images of tissue phantoms,” Phys. Med. Biol. 51(6), 1563–1575 (2006).
[Crossref] [PubMed]

K. W. Gossage, T. S. Tkaczyk, J. J. Rodriguez, and J. K. Barton, “Texture analysis of optical coherence tomography images: feasibility for tissue classification,” J. Biomed. Opt. 8(3), 570–575 (2003).
[Crossref] [PubMed]

Götzinger, E.

M. Pircher, E. Götzinger, 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]

Hariri, L. P.

K. W. Gossage, C. M. Smith, E. M. Kanter, L. P. Hariri, A. L. Stone, J. J. Rodriguez, S. K. Williams, and J. K. Barton, “Texture analysis of speckle in optical coherence tomography images of tissue phantoms,” Phys. Med. Biol. 51(6), 1563–1575 (2006).
[Crossref] [PubMed]

Hillman, T. R.

Hitzenberger, C.

Hitzenberger, C. K.

M. Pircher, E. Götzinger, 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]

Hong, Y. J.

Huang, Y.

Jarvi, M.

Jian, Z.

Jiang, J.

Kang, J. U.

Kanter, E. M.

K. W. Gossage, C. M. Smith, E. M. Kanter, L. P. Hariri, A. L. Stone, J. J. Rodriguez, S. K. Williams, and J. K. Barton, “Texture analysis of speckle in optical coherence tomography images of tissue phantoms,” Phys. Med. Biol. 51(6), 1563–1575 (2006).
[Crossref] [PubMed]

Kasaragod, D. K.

D. K. Kasaragod, Z. Lu, L. E. Smith, and S. J. Matcher, “Speckle texture analysis of optical coherence tomography images,” Proc. SPIE 7387, 73871V (2010).
[Crossref]

Kennedy, B. F.

Khurana, M.

Kiehl, T. R.

Kirby, M.

Ko, T. H.

Kurokawa, K.

Lee, J. S.

J. S. Lee, “Speckle analysis and smoothing of synthetic aperture radar images,” Comput. Graph. Image Process. 17(1), 24–32 (1981).
[Crossref]

Lee, K.

Lee, K. K. C.

Leitgeb, R.

R. Leitgeb, C. Hitzenberger, and A. Fercher, “Performance of fourier domain vs. time domain optical coherence tomography,” Opt. Express 11(8), 889–894 (2003).
[Crossref] [PubMed]

M. Pircher, E. Götzinger, 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]

Leung, M. K. K.

Liu, X.

Lopez, H.

R. F. Wagner, S. W. Smith, J. M. Sandrik, and H. Lopez, “Statistics of speckle in ultrasound B-scans,” IEEE Trans. Sonics Ultrason. 30(3), 156–163 (1983).
[Crossref]

Lu, Z.

D. K. Kasaragod, Z. Lu, L. E. Smith, and S. J. Matcher, “Speckle texture analysis of optical coherence tomography images,” Proc. SPIE 7387, 73871V (2010).
[Crossref]

Makita, S.

Mariampillai, A.

Marks, D. L.

Matcher, S. J.

D. K. Kasaragod, Z. Lu, L. E. Smith, and S. J. Matcher, “Speckle texture analysis of optical coherence tomography images,” Proc. SPIE 7387, 73871V (2010).
[Crossref]

Mathews, S. A.

Moriyama, E. H.

Motaghiannezam, R.

Motaghiannezam, S. M.

Munce, N. R.

Oh, W. Y.

Ozcan, A.

Pircher, M.

M. Pircher, E. Götzinger, 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]

Ralston, T. S.

Ramella-Roman, J. C.

Rao, B.

Rodriguez, J. J.

K. W. Gossage, C. M. Smith, E. M. Kanter, L. P. Hariri, A. L. Stone, J. J. Rodriguez, S. K. Williams, and J. K. Barton, “Texture analysis of speckle in optical coherence tomography images of tissue phantoms,” Phys. Med. Biol. 51(6), 1563–1575 (2006).
[Crossref] [PubMed]

K. W. Gossage, T. S. Tkaczyk, J. J. Rodriguez, and J. K. Barton, “Texture analysis of optical coherence tomography images: feasibility for tissue classification,” J. Biomed. Opt. 8(3), 570–575 (2003).
[Crossref] [PubMed]

Sampson, D. D.

Sandrik, J. M.

R. F. Wagner, S. W. Smith, J. M. Sandrik, and H. Lopez, “Statistics of speckle in ultrasound B-scans,” IEEE Trans. Sonics Ultrason. 30(3), 156–163 (1983).
[Crossref]

Schmitt, J. M.

J. M. Schmitt, S. H. Xiang, and K. M. Yung, “Speckle in optical coherence tomography,” J. Biomed. Opt. 4(1), 95–105 (1999).
[Crossref] [PubMed]

Sharma, U.

Smith, C. M.

K. W. Gossage, C. M. Smith, E. M. Kanter, L. P. Hariri, A. L. Stone, J. J. Rodriguez, S. K. Williams, and J. K. Barton, “Texture analysis of speckle in optical coherence tomography images of tissue phantoms,” Phys. Med. Biol. 51(6), 1563–1575 (2006).
[Crossref] [PubMed]

Smith, L. E.

D. K. Kasaragod, Z. Lu, L. E. Smith, and S. J. Matcher, “Speckle texture analysis of optical coherence tomography images,” Proc. SPIE 7387, 73871V (2010).
[Crossref]

Smith, S. W.

R. F. Wagner, S. W. Smith, J. M. Sandrik, and H. Lopez, “Statistics of speckle in ultrasound B-scans,” IEEE Trans. Sonics Ultrason. 30(3), 156–163 (1983).
[Crossref]

Standish, B. A.

Stone, A. L.

K. W. Gossage, C. M. Smith, E. M. Kanter, L. P. Hariri, A. L. Stone, J. J. Rodriguez, S. K. Williams, and J. K. Barton, “Texture analysis of speckle in optical coherence tomography images of tissue phantoms,” Phys. Med. Biol. 51(6), 1563–1575 (2006).
[Crossref] [PubMed]

Tearney, G. J.

Tkaczyk, T. S.

K. W. Gossage, T. S. Tkaczyk, J. J. Rodriguez, and J. K. Barton, “Texture analysis of optical coherence tomography images: feasibility for tissue classification,” J. Biomed. Opt. 8(3), 570–575 (2003).
[Crossref] [PubMed]

Tromberg, B. J.

Uribe-Patarroyo, N.

Vakoc, B. J.

Villiger, M.

Vitkin, A.

Vitkin, I. A.

Wagner, R. F.

R. F. Wagner, S. W. Smith, J. M. Sandrik, and H. Lopez, “Statistics of speckle in ultrasound B-scans,” IEEE Trans. Sonics Ultrason. 30(3), 156–163 (1983).
[Crossref]

Wang, R.

Wang, Y.

Williams, S. K.

K. W. Gossage, C. M. Smith, E. M. Kanter, L. P. Hariri, A. L. Stone, J. J. Rodriguez, S. K. Williams, and J. K. Barton, “Texture analysis of speckle in optical coherence tomography images of tissue phantoms,” Phys. Med. Biol. 51(6), 1563–1575 (2006).
[Crossref] [PubMed]

Wilson, B. C.

Xiang, S. H.

J. M. Schmitt, S. H. Xiang, and K. M. Yung, “Speckle in optical coherence tomography,” J. Biomed. Opt. 4(1), 95–105 (1999).
[Crossref] [PubMed]

Yang, V. X. D.

Yasuno, Y.

Yu, L.

Yung, K. M.

J. M. Schmitt, S. H. Xiang, and K. M. Yung, “Speckle in optical coherence tomography,” J. Biomed. Opt. 4(1), 95–105 (1999).
[Crossref] [PubMed]

Zhang, K.

Zhao, F.

Biomed. Opt. Express (5)

Comput. Graph. Image Process. (1)

J. S. Lee, “Speckle analysis and smoothing of synthetic aperture radar images,” Comput. Graph. Image Process. 17(1), 24–32 (1981).
[Crossref]

IEEE Trans. Sonics Ultrason. (1)

R. F. Wagner, S. W. Smith, J. M. Sandrik, and H. Lopez, “Statistics of speckle in ultrasound B-scans,” IEEE Trans. Sonics Ultrason. 30(3), 156–163 (1983).
[Crossref]

J. Biomed. Opt. (3)

J. M. Schmitt, S. H. Xiang, and K. M. Yung, “Speckle in optical coherence tomography,” J. Biomed. Opt. 4(1), 95–105 (1999).
[Crossref] [PubMed]

M. Pircher, E. Götzinger, 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]

K. W. Gossage, T. S. Tkaczyk, J. J. Rodriguez, and J. K. Barton, “Texture analysis of optical coherence tomography images: feasibility for tissue classification,” J. Biomed. Opt. 8(3), 570–575 (2003).
[Crossref] [PubMed]

J. Opt. Soc. Am. (1)

J. Opt. Soc. Am. A (2)

Opt. Express (6)

Opt. Lett. (7)

X. Liu, Y. Huang, J. C. Ramella-Roman, S. A. Mathews, and J. U. Kang, “Quantitative transverse flow measurement using optical coherence tomography speckle decorrelation analysis,” Opt. Lett. 38(5), 805–807 (2013).
[Crossref] [PubMed]

K. Kurokawa, S. Makita, Y. J. Hong, and Y. Yasuno, “In-plane and out-of-plane tissue micro-displacement measurement by correlation coefficients of optical coherence tomography,” Opt. Lett. 40(9), 2153–2156 (2015).
[Crossref] [PubMed]

A. Mariampillai, B. A. Standish, E. H. Moriyama, M. Khurana, N. R. Munce, M. K. K. Leung, J. Jiang, A. Cable, B. C. Wilson, I. A. Vitkin, and V. X. D. Yang, “Speckle variance detection of microvasculature using swept-source optical coherence tomography,” Opt. Lett. 33(13), 1530–1532 (2008).
[Crossref] [PubMed]

A. Mariampillai, M. K. K. Leung, M. Jarvi, B. A. Standish, K. Lee, B. C. Wilson, A. Vitkin, and V. X. D. Yang, “Optimized speckle variance OCT imaging of microvasculature,” Opt. Lett. 35(8), 1257–1259 (2010).
[Crossref] [PubMed]

Y. Wang and R. Wang, “Autocorrelation optical coherence tomography for mapping transverse particle-flow velocity,” Opt. Lett. 35(21), 3538–3540 (2010).
[Crossref] [PubMed]

B. F. Kennedy, T. R. Hillman, A. Curatolo, and D. D. Sampson, “Speckle reduction in optical coherence tomography by strain compounding,” Opt. Lett. 35(14), 2445–2447 (2010).
[Crossref] [PubMed]

D. C. Adler, T. H. Ko, and J. G. Fujimoto, “Speckle reduction in optical coherence tomography images by use of a spatially adaptive wavelet filter,” Opt. Lett. 29(24), 2878–2880 (2004).
[Crossref] [PubMed]

Phys. Med. Biol. (1)

K. W. Gossage, C. M. Smith, E. M. Kanter, L. P. Hariri, A. L. Stone, J. J. Rodriguez, S. K. Williams, and J. K. Barton, “Texture analysis of speckle in optical coherence tomography images of tissue phantoms,” Phys. Med. Biol. 51(6), 1563–1575 (2006).
[Crossref] [PubMed]

Proc. SPIE (1)

D. K. Kasaragod, Z. Lu, L. E. Smith, and S. J. Matcher, “Speckle texture analysis of optical coherence tomography images,” Proc. SPIE 7387, 73871V (2010).
[Crossref]

Other (2)

J. G. Webster, Medical Instrumentation Application and Design (Wiley 2010).

J. W. Goodman, Statistical Optics (Wiley, 1985).

Supplementary Material (3)

NameDescription
» Visualization 1: MP4 (234 KB)      Manually scanned imaging of phantom using adaptive speckle decorrelation
» Visualization 2: MP4 (167 KB)      Manually scanned imaging of phantom using speckle decorrelation between adjacent Ascans
» Visualization 3: MP4 (321 KB)      Manually scanned imaging of forearm skin using adaptive speckle decorrelation

Cited By

OSA participates in Crossref's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (12)

Fig. 1
Fig. 1 Person cross-correlation coefficient (XCC) versus lateral displacement δx. The same amount of uncertainty in calculating XCC results in different inaccuracy in estimating displacement δx.
Fig. 2
Fig. 2 Sensitivity S at different values of displacement.
Fig. 3
Fig. 3 (a) PDFs of OCT signals used for speckle decorrelation analysis and standard Rayleigh PDF; comparison between theoretical and experimental results for (a) XCC and (b) S at different displacements.
Fig. 4
Fig. 4 (a) XCC values calculated using Ascans with small displacements; (b) XCC values calculated using Ascans with medium displacements; (c) XCC values calculated using Ascans with large displacements; (d) displacements obtained using XCC values in Fig. 4(a); (e) displacements obtained using XCC values in Fig. 4(b); (f) displacements obtained using XCC values in Fig. 4(c).
Fig. 5
Fig. 5 Displacement estimation (circles) based on XCC between Ascans with fixed time intervals at different lateral scanning speeds; displacement estimation (triangles) based on adaptive XCC calculation for robust motion tracking at different lateral scanning speeds.
Fig. 6
Fig. 6 (a) 2D images of sequentially obtained Ascans; (b) estimated speed using small interval, large interval and adaptive speckle decorrelation analysis. 2D images of Ascans after distortion artifact corrected based on (c) the proposed adaptive speckle decorrelation analysis strategy, (d) speckle decorrelation with small time interval, (e) large time interval and (f) use the ground truth beam scanning speed.
Fig. 7
Fig. 7 (a) Calculation of cross-correlation between Ascan pairs acquired with different time intervals; (b) the value of XCC closest to ρmax is chose for robust motion tracking; (c) reconstruct distortion-free 2D OCT imaging and update display.
Fig. 8
Fig. 8 (a) Data processing flowchart for imaging reconstruction based on robust motion tracking using adaptive speckle decorrelation analysis.
Fig. 9
Fig. 9 (a) Photo of the phantom; (b) OCT image obtained by manual scanning; image reconstructed using XCCadaptive; (c) OCT image obtained by manual scanning; image reconstructed using XCCadj; (d) detecting edge of the ruling pattern in the image obtained using XCCadaptive through zero-crossing detection; (e) detecting edge of the ruling pattern in the image obtained using XCCadj through zero-crossing detection.
Fig. 10
Fig. 10 (a) Screen capture for OCT image reconstructed using XCCadaptive, Visualization 1; (b) screen capture for OCT image reconstructed using XCCadj, Visualization 2.
Fig. 11
Fig. 11 in vivo distortion-free image of skin obtained through robust motion tracking, from a healthy volunteer. (a) forearm, Visualization 3; (b) skin of fingertip; (c) volar of hand; (d) dorsum of hand. Scale bars indicate 250 μm.
Fig. 12
Fig. 12 Bscan image obtained from the phantom shown in Fig. 9(a), using a sample arm configuration based on galvanometer and scanning lens. Scale bars indicate 500μm.

Equations (5)

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

ρ( δx )=exp( δ x 2 ω 0 2 ).
ρ ^ = ρ ^ I t (z), I t+Δt (z) = [ I t (z) m t ][ I t+Δt ( z ) m t+Δt ] σ t σ t+Δt .
δ ^ = ω 0 ln( 1 ρ ^ ) .
S=| dρ dδx |=2 δx ω 0 2 exp( δ x 2 ω 0 2 ).
dS dδx = 2 ω 0 2 exp( δ x 2 ω 0 2 ) ( 2δx ) 2 ω 0 4 exp( δ x 2 ω 0 2 )=0.

Metrics