OSA's Digital Library

Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 5, Iss. 8 — Aug. 1, 2014
  • pp: 2591–2613

Quantitative 3D-OCT motion correction with tilt and illumination correction, robust similarity measure and regularization

Martin F. Kraus, Jonathan J. Liu, Julia Schottenhamml, Chieh-Li Chen, Attila Budai, Lauren Branchini, Tony Ko, Hiroshi Ishikawa, Gadi Wollstein, Joel Schuman, Jay S. Duker, James G. Fujimoto, and Joachim Hornegger  »View Author Affiliations


Biomedical Optics Express, Vol. 5, Issue 8, pp. 2591-2613 (2014)
http://dx.doi.org/10.1364/BOE.5.002591


View Full Text Article

Enhanced HTML    Acrobat PDF (3822 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

Variability in illumination, signal quality, tilt and the amount of motion pose challenges for post-processing based 3D-OCT motion correction algorithms. We present an advanced 3D-OCT motion correction algorithm using image registration and orthogonal raster scan patterns aimed at addressing these challenges. An intensity similarity measure using the pseudo Huber norm and a regularization scheme based on a pseudo L0.5 norm are introduced. A two-stage registration approach was developed. In the first stage, only axial motion and axial tilt are coarsely corrected. This result is then used as the starting point for a second stage full optimization. In preprocessing, a bias field estimation based approach to correct illumination differences in the input volumes is employed. Quantitative evaluation was performed using a large set of data acquired from 73 healthy and glaucomatous eyes using SD-OCT systems. OCT volumes of both the optic nerve head and the macula region acquired with three independent orthogonal volume pairs for each location were used to assess reproducibility. The advanced motion correction algorithm using the techniques presented in this paper was compared to a basic algorithm corresponding to an earlier version and to performing no motion correction. Errors in segmentation-based measures such as layer positions, retinal and nerve fiber thickness, as well as the blood vessel pattern were evaluated. The quantitative results consistently show that reproducibility is improved considerably by using the advanced algorithm, which also significantly outperforms the basic algorithm. The mean of the mean absolute retinal thickness difference over all data was 9.9 um without motion correction, 7.1 um using the basic algorithm and 5.0 um using the advanced algorithm. Similarly, the blood vessel likelihood map error is reduced to 69% of the uncorrected error for the basic and to 47% of the uncorrected error for the advanced algorithm. These results demonstrate that our advanced motion correction algorithm has the potential to improve the reliability of quantitative measurements derived from 3D-OCT data substantially.

© 2014 Optical Society of America

OCIS Codes
(100.2980) Image processing : Image enhancement
(100.5010) Image processing : Pattern recognition
(170.4470) Medical optics and biotechnology : Ophthalmology
(170.4500) Medical optics and biotechnology : Optical coherence tomography

ToC Category:
Category Pending

History
Original Manuscript: April 4, 2014
Revised Manuscript: May 30, 2014
Manuscript Accepted: June 4, 2014
Published: July 11, 2014

Citation
Martin F. Kraus, Jonathan J. Liu, Julia Schottenhamml, Chieh-Li Chen, Attila Budai, Lauren Branchini, Tony Ko, Hiroshi Ishikawa, Gadi Wollstein, Joel Schuman, Jay S. Duker, James G. Fujimoto, and Joachim Hornegger, "Quantitative 3D-OCT motion correction with tilt and illumination correction, robust similarity measure and regularization," Biomed. Opt. Express 5, 2591-2613 (2014)
http://www.opticsinfobase.org/boe/abstract.cfm?URI=boe-5-8-2591


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science254(5035), 1178–1181 (1991). [CrossRef] [PubMed]
  2. J. S. Schuman, Optical Coherence Tomography of Ocular Diseases, 3rd ed. (SLACK Inc., 2013).
  3. T. Klein, W. Wieser, R. Andre, T. Pfeiffer, C. M. Eigenwillig, and R. Huber, “Multi-MHz FDML OCT: snapshot retinal imaging at 6.7 million axial-scans per second,” Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine Xvi 8213(2012).
  4. B. Potsaid, V. Jayaraman, J. G. Fujimoto, J. Jiang, P. J. S. Heim, and A. E. Cable, “MEMS tunable VCSEL light source for ultrahigh speed 60kHz-1MHz axial scan rate and long range centimeter class OCT imaging,” Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XVI 8213(2012).
  5. B. Potsaid, I. Gorczynska, V. J. Srinivasan, Y. Chen, J. Jiang, A. Cable, and J. G. Fujimoto, “Ultrahigh speed spectral / Fourier domain OCT ophthalmic imaging at 70,000 to 312,500 axial scans per second,” Opt. Express16(19), 15149–15169 (2008). [CrossRef] [PubMed]
  6. R. D. Ferguson, D. X. Hammer, L. A. Paunescu, S. Beaton, and J. S. Schuman, “Tracking optical coherence tomography,” Opt. Lett.29(18), 2139–2141 (2004). [CrossRef] [PubMed]
  7. B. Braaf, K. V. Vienola, C. K. Sheehy, Q. Yang, K. A. Vermeer, P. Tiruveedhula, D. W. Arathorn, A. Roorda, and J. F. de Boer, “Real-time eye motion correction in phase-resolved OCT angiography with tracking SLO,” Biomed. Opt. Express4(1), 51–65 (2013). [CrossRef] [PubMed]
  8. K. V. Vienola, B. Braaf, C. K. Sheehy, Q. Yang, P. Tiruveedhula, D. W. Arathorn, J. F. de Boer, and A. Roorda, “Real-time eye motion compensation for OCT imaging with tracking SLO,” Biomed. Opt. Express3(11), 2950–2963 (2012). [CrossRef] [PubMed]
  9. S. Ricco, M. Chen, H. Ishikawa, G. Wollstein, and J. Schuman, “Correcting motion artifacts in retinal spectral domain optical coherence tomography via image registration,” Medical Image Computing and Computer-Assisted Intervention - Miccai 2009, Pt I, Proceedings 5761, 100–107 (2009).
  10. A. G. Capps, R. J. Zawadzki, Q. Yang, D. W. Arathorn, C. R. Vogel, B. Hamann, and J. S. Werner, “Correction of eye-motion artifacts in AO-OCT data sets,” Proc. SPIE7885, 78850D (2011). [CrossRef]
  11. M. F. Kraus, B. Potsaid, M. A. Mayer, R. Bock, B. Baumann, J. J. Liu, J. Hornegger, and J. G. Fujimoto, “Motion correction in optical coherence tomography volumes on a per A-scan basis using orthogonal scan patterns,” Biomed. Opt. Express3(6), 1182–1199 (2012). [CrossRef] [PubMed]
  12. H. C. Hendargo, R. Estrada, S. J. Chiu, C. Tomasi, S. Farsiu, and J. A. Izatt, “Automated non-rigid registration and mosaicing for robust imaging of distinct retinal capillary beds using speckle variance optical coherence tomography,” Biomed. Opt. Express4(6), 803–821 (2013). [CrossRef] [PubMed]
  13. R. J. Zawadzki, A. R. Fuller, S. S. Choi, D. F. Wiley, B. Hamann, and J. S. Werner, “Correction of motion artifacts and scanning beam distortions in 3D ophthalmic optical coherence tomography imaging,” Proc. SPIE6426, 642607 (2007). [CrossRef]
  14. N. Sebe, M. S. Lew, and D. P. Huijsmans, “Toward improved ranking metrics,” IEEE Trans. Pattern Anal. Mach. Intell.22(10), 1132–1143 (2000). [CrossRef]
  15. M. Bashkansky and J. Reintjes, “Statistics and reduction of speckle in optical coherence tomography,” Opt. Lett.25(8), 545–547 (2000). [CrossRef] [PubMed]
  16. P. J. Huber, “Robust estimation of a location parameter,” Ann. Math. Stat.35(1), 73–101 (1964). [CrossRef]
  17. K. Fountoulakis and J. Gondzio, “A second-order method for strongly convex L1-regularization problems,” arXiv preprint arXiv:1306.5386 (2013).
  18. Z. Hou, “A review on MR image intensity inhomogeneity correction,” Int. J. Biomed. Imaging2006, 49515 (2006). [CrossRef] [PubMed]
  19. 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. Express18(18), 19413–19428 (2010). [CrossRef] [PubMed]
  20. H. Ishikawa, M. L. Gabriele, G. Wollstein, R. D. Ferguson, D. X. Hammer, L. A. Paunescu, S. A. Beaton, and J. S. Schuman, “Retinal nerve fiber layer assessment using optical coherence tomography with active optic nerve head tracking,” Invest. Ophthalmol. Vis. Sci.47(3), 964–967 (2006). [CrossRef] [PubMed]
  21. M. L. Gabriele, H. Ishikawa, G. Wollstein, R. A. Bilonick, L. Kagemann, M. Wojtkowski, V. J. Srinivasan, J. G. Fujimoto, J. S. Duker, and J. S. Schuman, “Peripapillary nerve fiber layer thickness profile determined with high speed, ultrahigh resolution optical coherence tomography high-density scanning,” Invest. Ophthalmol. Vis. Sci.48(7), 3154–3160 (2007). [CrossRef] [PubMed]
  22. 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]
  23. A. F. Frangi, W. J. Niessen, K. L. Vincken, and M. A. Viergever, “Multiscale vessel enhancement filtering,” Lect. Notes Comput. Sci.1496, 130–137 (1998). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited