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Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 3, Iss. 8 — Aug. 1, 2012
  • pp: 1774–1786

Optics InfoBase > Biomedical Optics Express > Volume 3 > Issue 8 > Page 1774

Motion correction of in vivo three-dimensional optical coherence tomography of human skin using a fiducial marker

Yih Miin Liew, Robert A. McLaughlin, Fiona M. Wood, and David D. Sampson  »View Author Affiliations


Biomedical Optics Express, Vol. 3, Issue 8, pp. 1774-1786 (2012)
http://dx.doi.org/10.1364/BOE.3.001774


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Abstract

This paper presents a novel method based on a fiducial marker for correction of motion artifacts in 3D, in vivo, optical coherence tomography (OCT) scans of human skin and skin scars. The efficacy of this method was compared against a standard cross-correlation intensity-based registration method. With a fiducial marker adhered to the skin, OCT scans were acquired using two imaging protocols: direct imaging from air into tissue; and imaging through ultrasound gel into tissue, which minimized the refractive index mismatch at the tissue surface. The registration methods were assessed with data from both imaging protocols and showed reduced distortion of skin features due to motion. The fiducial-based method was found to be more accurate and robust, with an average RMS error below 20 µm and success rate above 90%. In contrast, the intensity-based method had an average RMS error ranging from 36 to 45 µm, and a success rate from 50% to 86%. The intensity-based algorithm was found to be particularly confounded by corrugations in the skin. By contrast, tissue features did not affect the fiducial-based method, as the motion correction was based on delineation of the flat fiducial marker. The average computation time for the fiducial-based algorithm was approximately 21 times less than for the intensity-based algorithm.

© 2012 OSA

OCIS Codes
(100.2000) Image processing : Digital image processing
(100.6950) Image processing : Tomographic image processing
(170.4500) Medical optics and biotechnology : Optical coherence tomography

ToC Category:
Image Processing

History
Original Manuscript: May 2, 2012
Revised Manuscript: June 21, 2012
Manuscript Accepted: June 26, 2012
Published: June 29, 2012

Citation
Yih Miin Liew, Robert A. McLaughlin, Fiona M. Wood, and David D. Sampson, "Motion correction of in vivo three-dimensional optical coherence tomography of human skin using a fiducial marker," Biomed. Opt. Express 3, 1774-1786 (2012)
http://www.opticsinfobase.org/boe/abstract.cfm?URI=boe-3-8-1774


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References

  1. J. Welzel, E. Lankenau, R. Birngruber, and R. Engelhardt, “Optical coherence tomography of the human skin,” J. Am. Acad. Dermatol.37(6), 958–963 (1997). [CrossRef] [PubMed]
  2. T. Gambichler, V. Jaedicke, and S. Terras, “Optical coherence tomography in dermatology: technical and clinical aspects,” Arch. Dermatol. Res.303(7), 457–473 (2011). [CrossRef] [PubMed]
  3. M. Mogensen, L. Thrane, T. M. Joergensen, P. E. Andersen, and G. B. E. Jemec, “Optical coherence tomography for imaging of skin and skin diseases,” Semin. Cutan. Med. Surg.28(3), 196–202 (2009). [CrossRef] [PubMed]
  4. R. Steiner, K. Kunzi-Rapp, and K. Scharffetter-Kochanek, “Optical coherence tomography: clinical applications in dermatology,” Med. Laser Appl.18(3), 249–259 (2003). [CrossRef]
  5. M. Mogensen, B. M. Nürnberg, J. L. Forman, J. B. Thomsen, L. Thrane, and G. B. Jemec, “In vivo thickness measurement of basal cell carcinoma and actinic keratosis with optical coherence tomography and 20-MHz ultrasound,” Br. J. Dermatol.160(5), 1026–1033 (2009). [CrossRef] [PubMed]
  6. T. Gambichler, B. Künzlberger, V. Paech, A. Kreuter, S. Boms, A. Bader, G. Moussa, M. Sand, P. Altmeyer, and K. Hoffmann, “UVA1 and UVB irradiated skin investigated by optical coherence tomography in vivo: a preliminary study,” Clin. Exp. Dermatol.30(1), 79–82 (2005). [CrossRef] [PubMed]
  7. S. Sakai, M. Yamanari, A. Miyazawa, M. Matsumoto, N. Nakagawa, T. Sugawara, K. Kawabata, T. Yatagai, and Y. Yasuno, “In vivo three-dimensional birefringence analysis shows collagen differences between young and old photo-aged human skin,” J. Invest. Dermatol.128(7), 1641–1647 (2008). [CrossRef] [PubMed]
  8. C. Salvini, D. Massi, A. Cappetti, M. Stante, P. Cappugi, P. Fabbri, and P. Carli, “Application of optical coherence tomography in non-invasive characterization of skin vascular lesions,” Skin Res. Technol.14(1), 89–92 (2008). [PubMed]
  9. S. A. Coulman, J. C. Birchall, A. Alex, M. Pearton, B. Hofer, C. O’Mahony, W. Drexler, and B. Považay, “In vivo, in situ imaging of microneedle insertion into the skin of human volunteers using optical coherence tomography,” Pharm. Res.28(1), 66–81 (2011). [CrossRef] [PubMed]
  10. H. Morsy, S. Kamp, L. Thrane, N. Behrendt, B. Saunder, H. Zayan, E. A. Elmagid, and G. B. Jemec, “Optical coherence tomography imaging of psoriasis vulgaris: correlation with histology and disease severity,” Arch. Dermatol. Res.302(2), 105–111 (2010). [CrossRef] [PubMed]
  11. T. Hinz, L. K. Ehler, H. Voth, I. Fortmeier, T. Hoeller, T. Hornung, and M. H. Schmid-Wendtner, “Assessment of tumor thickness in melanocytic skin lesions: comparison of optical coherence tomography, 20-MHz ultrasound and histopathology,” Dermatology223(2), 161–168 (2011). [CrossRef] [PubMed]
  12. A. Alex, B. Povazay, B. Hofer, S. Popov, C. Glittenberg, S. Binder, and W. Drexler, “Multispectral in vivo three-dimensional optical coherence tomography of human skin,” J. Biomed. Opt.15(2), 026025 (2010). [CrossRef] [PubMed]
  13. M. Mogensen, H. A. Morsy, L. Thrane, and G. B. E. Jemec, “Morphology and epidermal thickness of normal skin imaged by optical coherence tomography,” Dermatology217(1), 14–20 (2008). [CrossRef] [PubMed]
  14. J. Enfield, E. Jonathan, and M. Leahy, “In vivo imaging of the microcirculation of the volar forearm using correlation mapping optical coherence tomography (cmOCT),” Biomed. Opt. Express2(5), 1184–1193 (2011). [CrossRef] [PubMed]
  15. E. Z. Zhang, B. Povazay, J. Laufer, A. Alex, B. Hofer, B. Pedley, C. Glittenberg, B. Treeby, B. Cox, P. Beard, and W. Drexler, “Multimodal photoacoustic and optical coherence tomography scanner using an all optical detection scheme for 3D morphological skin imaging,” Biomed. Opt. Express2(8), 2202–2215 (2011). [CrossRef] [PubMed]
  16. M. Mogensen, T. M. Joergensen, B. M. Nürnberg, H. A. Morsy, J. B. Thomsen, L. Thrane, and G. B. E. Jemec, “Assessment of optical coherence tomography imaging in the diagnosis of non-melanoma skin cancer and benign lesions versus normal skin: observer-blinded evaluation by dermatologists and pathologists,” Dermatol. Surg.35(6), 965–972 (2009). [CrossRef] [PubMed]
  17. A. M. Forsea, E. M. Carstea, L. Ghervase, C. Giurcaneanu, and G. Pavelescu, “Clinical application of optical coherence tomography for the imaging of non-melanocytic cutaneous tumors: a pilot multi-modal study,” J. Med. Life3(4), 381–389 (2010). [PubMed]
  18. S. Ricco, M. Chen, H. Ishikawa, G. Wollstein, and J. Schuman, “Correcting motion artifacts in retinal spectral domain optical coherence tomography via image registration,” in Medical Image Computing and Computer-Assisted Intervention—MICCAI 2009 (Springer, 2009), pp. 100–107.
  19. 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]
  20. 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]
  21. B. Antony, M. D. Abràmoff, L. Tang, W. D. Ramdas, J. R. Vingerling, N. M. Jansonius, K. Lee, Y. H. Kwon, M. Sonka, and M. K. Garvin, “Automated 3-D method for the correction of axial artifacts in spectral-domain optical coherence tomography images,” Biomed. Opt. Express2(8), 2403–2416 (2011). [CrossRef] [PubMed]
  22. W. Kang, H. Wang, Z. Wang, M. W. Jenkins, G. A. Isenberg, A. Chak, and A. M. Rollins, “Motion artifacts associated with in vivo endoscopic OCT images of the esophagus,” Opt. Express19(21), 20722–20735 (2011). [CrossRef] [PubMed]
  23. R. A. McLaughlin, J. J. Armstrong, S. Becker, J. H. Walsh, A. Jain, D. R. Hillman, P. R. Eastwood, and D. D. Sampson, “Respiratory gating of anatomical optical coherence tomography images of the human airway,” Opt. Express17(8), 6568–6577 (2009). [CrossRef] [PubMed]
  24. M. W. Jenkins, O. Q. Chughtai, A. N. Basavanhally, M. Watanabe, and A. M. Rollins, “In vivo gated 4D imaging of the embryonic heart using optical coherence tomography,” J. Biomed. Opt.12(3), 030505 (2007). [CrossRef] [PubMed]
  25. T. Klein, W. Wieser, C. M. Eigenwillig, B. R. Biedermann, and R. Huber, “Megahertz OCT for ultrawide-field retinal imaging with a 1050 nm Fourier domain mode-locked laser,” Opt. Express19(4), 3044–3062 (2011). [CrossRef] [PubMed]
  26. D. L. G. Hill, P. G. Batchelor, M. Holden, and D. J. Hawkes, “Medical image registration,” Phys. Med. Biol.46(3), R1–R45 (2001). [CrossRef] [PubMed]
  27. G. P. Penney, J. Weese, J. A. Little, P. Desmedt, D. L. G. Hill, and D. J. Hawkes, “A comparison of similarity measures for use in 2-D-3-D medical image registration,” IEEE Trans. Med. Imaging17(4), 586–595 (1998). [CrossRef] [PubMed]
  28. 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]
  29. R. A. McLaughlin, J. Hipwell, D. J. Hawkes, J. A. Noble, J. V. Byrne, and T. C. Cox, “A comparison of a similarity-based and a feature-based 2-D-3-D registration method for neurointerventional use,” IEEE Trans. Med. Imaging24(8), 1058–1066 (2005). [CrossRef] [PubMed]
  30. Y. Li, G. Gregori, R. W. Knighton, B. J. Lujan, and P. J. Rosenfeld, “Registration of OCT fundus images with color fundus photographs based on blood vessel ridges,” Opt. Express19(1), 7–16 (2011). [CrossRef] [PubMed]
  31. Y. M. Liew, R. A. McLaughlin, F. M. Wood, and D. D. Sampson, “Reduction of image artifacts in three-dimensional optical coherence tomography of skin in vivo,” J. Biomed. Opt.16(11), 116018 (2011). [CrossRef] [PubMed]
  32. A. Bayat, D. A. McGrouther, and M. W. J. Ferguson, “Skin scarring,” BMJ326(7380), 88–92 (2003). [CrossRef] [PubMed]
  33. T. Amadeu, A. Braune, C. Mandarim-de-Lacerda, L. C. Porto, A. Desmoulière, and A. Costa, “Vascularization pattern in hypertrophic scars and keloids: a stereological analysis,” Pathol. Res. Pract.199(7), 469–473 (2003). [CrossRef] [PubMed]
  34. R. O. Duda and P. E. Hart, “Use of the Hough transformation to detect lines and curves in pictures,” Commun. ACM15(1), 11–15 (1972). [CrossRef]
  35. S. Golemati, J. Stoitsis, E. G. Sifakis, T. Balkizas, and K. S. Nikita, “Using the Hough transform to segment ultrasound images of longitudinal and transverse sections of the carotid artery,” Ultrasound Med. Biol.33(12), 1918–1932 (2007). [CrossRef] [PubMed]
  36. Y. M. Zhu, S. M. Cochoff, and R. Sukalac, “Automatic patient table removal in CT images,” J. Digit. Imaging (2012), 6 pages, online first. [PubMed]
  37. R. M. Lewis and V. Torczon, “Pattern search algorithms for bound constrained minimization,” SIAM J. Optim.9(4), 1082–1099 (1999). [CrossRef]
  38. G. K. Rohde, A. Aldroubi, and D. M. Healy., “Interpolation artifacts in sub-pixel image registration,” IEEE Trans. Image Process.18(2), 333–345 (2009). [CrossRef] [PubMed]
  39. E. R. Davies, Machine Vision: Theory, Algorithms, Practicalities, 3rd ed. (Academic, 2005), Chap. 9.

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