Scatterer size-based analysis of optical coherence tomography images using spectral estimation techniques

Andreas Kartakoullis; Evgenia Bousi; Costas Pitris

doi:10.1364/OE.18.009181

Scatterer size-based analysis of optical coherence tomography images using spectral estimation techniques

Andreas Kartakoullis, Evgenia Bousi, and Costas Pitris

Optics Express
Vol. 18,
Issue 9,
pp. 9181-9191
(2010)
•https://doi.org/10.1364/OE.18.009181

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Andreas Kartakoullis, Evgenia Bousi, and Costas Pitris, "Scatterer size-based analysis of optical coherence tomography images using spectral estimation techniques," Opt. Express 18, 9181-9191 (2010)

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Related Topics
Table of Contents Category
- Imaging Systems
Optics & Photonics Topics
?

The topics in this list come from the OSA Optics and Photonics Topics applied to this article.
Previously assigned OCIS codes
- Optical coherence tomography (110.4500)
- Lasers, tunable (140.3600)
- Medical and biological imaging (170.3880)
- Optical coherence tomography (170.4500)
- Scattering (290.0290)

About this Article
History
- Original Manuscript: February 17, 2010
- Revised Manuscript: April 7, 2010
- Manuscript Accepted: April 12, 2010
- Published: April 16, 2010
Virtual Issues
Virtual Journal for Biomedical Optics Vol. 5, Iss. 9

Accessible

Open Access

Abstract

A novel spectral analysis technique of OCT images is demonstrated in this paper for classification and scatterer size estimation. It is based on SOCT autoregressive spectral estimation techniques and statistical analysis. Two different statistical analysis methods were applied to OCT images acquired from tissue phantoms, the first method required prior information on the sample for variance analysis of the spectral content. The second method used k-means clustering without prior information for the sample. The results are very encouraging and indicate that the spectral content of OCT signals can be used to estimate scatterer size and to classify dissimilar areas in phantoms and tissues with sensitivity and specificity of more than 90%.

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References

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|
Year
|
Author
|
Publication

D. J. Stephens and V. J. Allan, “Light microscopy techniques for live cell imaging,” Science 300(5616), 82–86 (2003).
[Crossref] [PubMed]
H. C. V. de Hulst, Light Scattering by Small Particles (Dover Publications, New York, 1981).
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[Crossref] [PubMed]
L. Perelman, V. Backman, M. Wallace, G. Zonios, R. Manoharan, A. Nusrat, S. Shields, M. Seiler, C. Lima, T. Hamano, I. Itzkan, J. Van Dam, J. Crawford, and M. Feld, “Observation of periodic fine structure in reflectance from biological tissue a new technique for measuring nuclear size distribution,” Phys. Rev. Lett. 80(3), 627–630 (1998).
[Crossref]
V. Backman, V. Gopal, M. Kalashnikov, K. Badizadegan, R. Gurjar, A. Wax, I. Georgakoudi, M. Mueller, C. Boone, R. Dasari, and M. Feld, “Measuring cellular structure at submicrometer scale with light scattering spectroscopy,” IEEE Sel. Top Quantum Electron. 7(6), 887–893 (2001).
[Crossref]
M. B. Wallace, L. T. Perelman, V. Backman, J. M. Crawford, M. Fitzmaurice, M. Seiler, K. Badizadegan, S. J. Shields, I. Itzkan, R. R. Dasari, J. Van Dam, and M. S. Feld, “Endoscopic detection of dysplasia in patients with Barrett’s esophagus using light-scattering spectroscopy,” Gastroenterology 119(3), 677–682 (2000).
[Crossref] [PubMed]
M. S. Feld, V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, and J. Van Dam, “Detection of preinvasive cancer cells,” Nature 406(6791), 35–36 (2000).
[Crossref] [PubMed]
A. Wax, C. Yang, and J. A. Izatt, “Fourier-domain low-coherence interferometry for light-scattering spectroscopy,” Opt. Lett. 28(14), 1230–1232 (2003).
[Crossref] [PubMed]
A. Wax, C. Yang, V. Backman, M. Kalashnikov, R. R. Dasari, and M. S. Feld, “Determination of particle size by using the angular distribution of backscattered light as measured with low-coherence interferometry,” J. Opt. Soc. Am. A 19(4), 737–744 (2002).
[Crossref]
U. Morgner, W. Drexler, F. X. Kärtner, X. D. Li, C. Pitris, E. P. Ippen, and J. G. Fujimoto, “Spectroscopic optical coherence tomography,” Opt. Lett. 25(2), 111–113 (2000).
[Crossref]
D. J. Faber, E. G. Mik, M. C. G. Aalders, and T. G. van Leeuwen, “Light absorption of (oxy-)hemoglobin assessed by spectroscopic optical coherence tomography,” Opt. Lett. 28(16), 1436–1438 (2003).
[Crossref] [PubMed]
C. Xu, J. Ye, D. L. Marks, and S. A. Boppart, “Near-infrared dyes as contrast-enhancing agents for spectroscopic optical coherence tomography,” Opt. Lett. 29(14), 1647–1649 (2004).
[Crossref] [PubMed]
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[Crossref] [PubMed]
D. Adler, T. Ko, P. Herz, and J. Fujimoto, “Optical coherence tomography contrast enhancement using spectroscopic analysis with spectral autocorrelation,” Opt. Express 12(22), 5487–5501 (2004).
[Crossref] [PubMed]
C. Xu, P. Carney, and S. Boppart, “Wavelength-dependent scattering in spectroscopic optical coherence tomography,” Opt. Express 13(14), 5450–5462 (2005).
[Crossref] [PubMed]
C. Xu, P. S. Carney, W. Tan, and S. A. Boppart, “Light-scattering spectroscopic optical coherence tomography for differentiating cells in 3D cell culture,” Proc. SPIE 6088(608804), 1–10 (2006).
I. V. Turchin, E. A. Sergeeva, L. S. Dolin, V. A. Kamensky, N. M. Shakhova, and R. Richards-Kortum, “Novel algorithm of processing optical coherence tomography images for differentiation of biological tissue pathologies,” J. Biomed. Opt. 10(6), 064024 (2005).
[Crossref]
X. Qi, M. V. Sivak, G. Isenberg, J. E. Willis, and A. M. Rollins, “Computer-aided diagnosis of dysplasia in Barrett’s esophagus using endoscopic optical coherence tomography,” J. Biomed. Opt. 11(4), 044010 (2006).
[Crossref] [PubMed]
C. A. Lingley-Papadopoulos, M. H. Loew, M. J. Manyak, and J. M. Zara, “Computer recognition of cancer in the urinary bladder using optical coherence tomography and texture analysis,” J. Biomed. Opt. 13(2), 024003 (2008).
[Crossref] [PubMed]
A. Dunn and R. Richards-Kortum, “Three-dimensional computation of light scattering from cells,” IEEE J. Sel. Top. Quantum Electron. 2(4), 898–905 (1996).
[Crossref]
F. Bazant-Hegemark and N. Stone, “Near real-time classification of optical coherence tomography data using principal components fed linear discriminant analysis,” J. Biomed. Opt. 13(3), 034002 (2008).
[Crossref] [PubMed]
C. Pitris, A. Kartakoullis, and E. Bousi, “AM-FM techniques in the analysis of optical coherence tomography signals,” J. Biophoton. 2(6–7), 364–369 (2009).
[Crossref]
C. Xu, F. Kamalabadi, and S. A. Boppart, “Comparative performance analysis of time-frequency distributions for spectroscopic optical coherence tomography,” Appl. Opt. 44(10), 1813–1822 (2005).
[Crossref] [PubMed]
P. Chaturvedi and M. F. Insana, “Autoregressive spectral estimation in ultrasonic scatterer size imaging,” Ultrason. Imaging 18(1), 10–24 (1996).
[Crossref] [PubMed]
K. Wear, R. Wagner, and B. Garra, “A comparison of autoregressive spectral estimation algorithms and order determination methods in ultrasonic tissue characterization,” Ultrasonics, Ferroelectrics and Frequency Control, IEEE Transactions on 42(4), 709–716 (1995).
[Crossref]
J. Proakis and D. Manolakis, Digital Signal Processing, Principles, Algorithms and Applications (Prentice Hall, 2006).
P. Stoica and R. L. Moses, Introduction to Spectral Analysis (Prentice Hall, 1997).
R. N. Graf and A. Wax, “Temporal coherence and time-frequency distributions in spectroscopic optical coherence tomography,” J. Opt. Soc. Am. A 24(8), 2186–2195 (2007).
[Crossref]
I. T. Jolliffe, Principal Component Analysis, 2nd ed. (Springer-Verlag, 2002).
J. B. MacQueen, “Some Methods for classification and Analysis of Multivariate Observations,” Proceedings of 5-th Berkeley Symposium on Mathematical Statistics and Probability, University of California Press1, 281–297 (1967).
A. M. Zysk and S. A. Boppart, “Computational methods for analysis of human breast tumor tissue in optical coherence tomography images,” J. Biomed. Opt. 11(5), 054015 (2006).
[Crossref] [PubMed]
C. L. Tsai, J. C. Chen, and W. J. Wang, “Near-infrared Absorption Property of Biological Soft Tissue Constituents,” J. Med. Bio. Eng. 21(1), 7–14 (2001).

2009 (1)

C. Pitris, A. Kartakoullis, and E. Bousi, “AM-FM techniques in the analysis of optical coherence tomography signals,” J. Biophoton. 2(6–7), 364–369 (2009).
[Crossref]

2008 (2)

C. A. Lingley-Papadopoulos, M. H. Loew, M. J. Manyak, and J. M. Zara, “Computer recognition of cancer in the urinary bladder using optical coherence tomography and texture analysis,” J. Biomed. Opt. 13(2), 024003 (2008).
[Crossref] [PubMed]

F. Bazant-Hegemark and N. Stone, “Near real-time classification of optical coherence tomography data using principal components fed linear discriminant analysis,” J. Biomed. Opt. 13(3), 034002 (2008).
[Crossref] [PubMed]

2007 (1)

R. N. Graf and A. Wax, “Temporal coherence and time-frequency distributions in spectroscopic optical coherence tomography,” J. Opt. Soc. Am. A 24(8), 2186–2195 (2007).
[Crossref]

2006 (3)

A. M. Zysk and S. A. Boppart, “Computational methods for analysis of human breast tumor tissue in optical coherence tomography images,” J. Biomed. Opt. 11(5), 054015 (2006).
[Crossref] [PubMed]

C. Xu, P. S. Carney, W. Tan, and S. A. Boppart, “Light-scattering spectroscopic optical coherence tomography for differentiating cells in 3D cell culture,” Proc. SPIE 6088(608804), 1–10 (2006).

X. Qi, M. V. Sivak, G. Isenberg, J. E. Willis, and A. M. Rollins, “Computer-aided diagnosis of dysplasia in Barrett’s esophagus using endoscopic optical coherence tomography,” J. Biomed. Opt. 11(4), 044010 (2006).
[Crossref] [PubMed]

2005 (3)

I. V. Turchin, E. A. Sergeeva, L. S. Dolin, V. A. Kamensky, N. M. Shakhova, and R. Richards-Kortum, “Novel algorithm of processing optical coherence tomography images for differentiation of biological tissue pathologies,” J. Biomed. Opt. 10(6), 064024 (2005).
[Crossref]

C. Xu, F. Kamalabadi, and S. A. Boppart, “Comparative performance analysis of time-frequency distributions for spectroscopic optical coherence tomography,” Appl. Opt. 44(10), 1813–1822 (2005).
[Crossref] [PubMed]

C. Xu, P. Carney, and S. Boppart, “Wavelength-dependent scattering in spectroscopic optical coherence tomography,” Opt. Express 13(14), 5450–5462 (2005).
[Crossref] [PubMed]

2004 (3)

B. Hermann, K. Bizheva, A. Unterhuber, B. Povazay, H. Sattmann, L. Schmetterer, A. Fercher, and W. Drexler, “Precision of extracting absorption profiles from weakly scattering media with spectroscopic time-domain optical coherence tomography,” Opt. Express 12(8), 1677–1688 (2004).
[Crossref] [PubMed]

C. Xu, J. Ye, D. L. Marks, and S. A. Boppart, “Near-infrared dyes as contrast-enhancing agents for spectroscopic optical coherence tomography,” Opt. Lett. 29(14), 1647–1649 (2004).
[Crossref] [PubMed]

D. Adler, T. Ko, P. Herz, and J. Fujimoto, “Optical coherence tomography contrast enhancement using spectroscopic analysis with spectral autocorrelation,” Opt. Express 12(22), 5487–5501 (2004).
[Crossref] [PubMed]

2003 (3)

A. Wax, C. Yang, and J. A. Izatt, “Fourier-domain low-coherence interferometry for light-scattering spectroscopy,” Opt. Lett. 28(14), 1230–1232 (2003).
[Crossref] [PubMed]

D. J. Faber, E. G. Mik, M. C. G. Aalders, and T. G. van Leeuwen, “Light absorption of (oxy-)hemoglobin assessed by spectroscopic optical coherence tomography,” Opt. Lett. 28(16), 1436–1438 (2003).
[Crossref] [PubMed]

D. J. Stephens and V. J. Allan, “Light microscopy techniques for live cell imaging,” Science 300(5616), 82–86 (2003).
[Crossref] [PubMed]

2002 (1)

A. Wax, C. Yang, V. Backman, M. Kalashnikov, R. R. Dasari, and M. S. Feld, “Determination of particle size by using the angular distribution of backscattered light as measured with low-coherence interferometry,” J. Opt. Soc. Am. A 19(4), 737–744 (2002).
[Crossref]

2001 (2)

C. L. Tsai, J. C. Chen, and W. J. Wang, “Near-infrared Absorption Property of Biological Soft Tissue Constituents,” J. Med. Bio. Eng. 21(1), 7–14 (2001).

V. Backman, V. Gopal, M. Kalashnikov, K. Badizadegan, R. Gurjar, A. Wax, I. Georgakoudi, M. Mueller, C. Boone, R. Dasari, and M. Feld, “Measuring cellular structure at submicrometer scale with light scattering spectroscopy,” IEEE Sel. Top Quantum Electron. 7(6), 887–893 (2001).
[Crossref]

2000 (3)

M. B. Wallace, L. T. Perelman, V. Backman, J. M. Crawford, M. Fitzmaurice, M. Seiler, K. Badizadegan, S. J. Shields, I. Itzkan, R. R. Dasari, J. Van Dam, and M. S. Feld, “Endoscopic detection of dysplasia in patients with Barrett’s esophagus using light-scattering spectroscopy,” Gastroenterology 119(3), 677–682 (2000).
[Crossref] [PubMed]

M. S. Feld, V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, and J. Van Dam, “Detection of preinvasive cancer cells,” Nature 406(6791), 35–36 (2000).
[Crossref] [PubMed]

U. Morgner, W. Drexler, F. X. Kärtner, X. D. Li, C. Pitris, E. P. Ippen, and J. G. Fujimoto, “Spectroscopic optical coherence tomography,” Opt. Lett. 25(2), 111–113 (2000).
[Crossref]

1998 (1)

L. Perelman, V. Backman, M. Wallace, G. Zonios, R. Manoharan, A. Nusrat, S. Shields, M. Seiler, C. Lima, T. Hamano, I. Itzkan, J. Van Dam, J. Crawford, and M. Feld, “Observation of periodic fine structure in reflectance from biological tissue a new technique for measuring nuclear size distribution,” Phys. Rev. Lett. 80(3), 627–630 (1998).
[Crossref]

1996 (3)

J. Beuthan, O. Minet, J. Helfmann, M. Herrig, and G. Müller, “The spatial variation of the refractive index in biological cells,” Phys. Med. Biol. 41(3), 369–382 (1996).
[Crossref] [PubMed]

A. Dunn and R. Richards-Kortum, “Three-dimensional computation of light scattering from cells,” IEEE J. Sel. Top. Quantum Electron. 2(4), 898–905 (1996).
[Crossref]

P. Chaturvedi and M. F. Insana, “Autoregressive spectral estimation in ultrasonic scatterer size imaging,” Ultrason. Imaging 18(1), 10–24 (1996).
[Crossref] [PubMed]

1995 (1)

K. Wear, R. Wagner, and B. Garra, “A comparison of autoregressive spectral estimation algorithms and order determination methods in ultrasonic tissue characterization,” Ultrasonics, Ferroelectrics and Frequency Control, IEEE Transactions on 42(4), 709–716 (1995).
[Crossref]

Aalders, M. C. G.

Adler, D.

Allan, V. J.

D. J. Stephens and V. J. Allan, “Light microscopy techniques for live cell imaging,” Science 300(5616), 82–86 (2003).
[Crossref] [PubMed]

Arendt, J. T.

Backman, V.

Badizadegan, K.

Bazant-Hegemark, F.

Beuthan, J.

J. Beuthan, O. Minet, J. Helfmann, M. Herrig, and G. Müller, “The spatial variation of the refractive index in biological cells,” Phys. Med. Biol. 41(3), 369–382 (1996).
[Crossref] [PubMed]

Bizheva, K.

Bohren, C.

C. Bohren and D. Huffman, Absorption and Scattering of Light by Small Particles, Wiley Science Paperback Series (John Wiley and Sons, New York, 1998).

Boone, C.

Boppart, S.

C. Xu, P. Carney, and S. Boppart, “Wavelength-dependent scattering in spectroscopic optical coherence tomography,” Opt. Express 13(14), 5450–5462 (2005).
[Crossref] [PubMed]

Boppart, S. A.

A. M. Zysk and S. A. Boppart, “Computational methods for analysis of human breast tumor tissue in optical coherence tomography images,” J. Biomed. Opt. 11(5), 054015 (2006).
[Crossref] [PubMed]

C. Xu, P. S. Carney, W. Tan, and S. A. Boppart, “Light-scattering spectroscopic optical coherence tomography for differentiating cells in 3D cell culture,” Proc. SPIE 6088(608804), 1–10 (2006).

Bousi, E.

C. Pitris, A. Kartakoullis, and E. Bousi, “AM-FM techniques in the analysis of optical coherence tomography signals,” J. Biophoton. 2(6–7), 364–369 (2009).
[Crossref]

Carney, P.

C. Xu, P. Carney, and S. Boppart, “Wavelength-dependent scattering in spectroscopic optical coherence tomography,” Opt. Express 13(14), 5450–5462 (2005).
[Crossref] [PubMed]

Carney, P. S.

C. Xu, P. S. Carney, W. Tan, and S. A. Boppart, “Light-scattering spectroscopic optical coherence tomography for differentiating cells in 3D cell culture,” Proc. SPIE 6088(608804), 1–10 (2006).

Chaturvedi, P.

P. Chaturvedi and M. F. Insana, “Autoregressive spectral estimation in ultrasonic scatterer size imaging,” Ultrason. Imaging 18(1), 10–24 (1996).
[Crossref] [PubMed]

Chen, J. C.

C. L. Tsai, J. C. Chen, and W. J. Wang, “Near-infrared Absorption Property of Biological Soft Tissue Constituents,” J. Med. Bio. Eng. 21(1), 7–14 (2001).

Crawford, J.

Crawford, J. M.

Dasari, R.

Dasari, R. R.

de Hulst, H. C. V.

H. C. V. de Hulst, Light Scattering by Small Particles (Dover Publications, New York, 1981).

Dolin, L. S.

Drexler, W.

U. Morgner, W. Drexler, F. X. Kärtner, X. D. Li, C. Pitris, E. P. Ippen, and J. G. Fujimoto, “Spectroscopic optical coherence tomography,” Opt. Lett. 25(2), 111–113 (2000).
[Crossref]

Dunn, A.

A. Dunn and R. Richards-Kortum, “Three-dimensional computation of light scattering from cells,” IEEE J. Sel. Top. Quantum Electron. 2(4), 898–905 (1996).
[Crossref]

Faber, D. J.

Feld, M.

Feld, M. S.

Fercher, A.

Fitzmaurice, M.

Fujimoto, J.

Fujimoto, J. G.

U. Morgner, W. Drexler, F. X. Kärtner, X. D. Li, C. Pitris, E. P. Ippen, and J. G. Fujimoto, “Spectroscopic optical coherence tomography,” Opt. Lett. 25(2), 111–113 (2000).
[Crossref]

Garra, B.

Georgakoudi, I.

Gopal, V.

Graf, R. N.

R. N. Graf and A. Wax, “Temporal coherence and time-frequency distributions in spectroscopic optical coherence tomography,” J. Opt. Soc. Am. A 24(8), 2186–2195 (2007).
[Crossref]

Gurjar, R.

Hamano, T.

Helfmann, J.

J. Beuthan, O. Minet, J. Helfmann, M. Herrig, and G. Müller, “The spatial variation of the refractive index in biological cells,” Phys. Med. Biol. 41(3), 369–382 (1996).
[Crossref] [PubMed]

Hermann, B.

Herrig, M.

J. Beuthan, O. Minet, J. Helfmann, M. Herrig, and G. Müller, “The spatial variation of the refractive index in biological cells,” Phys. Med. Biol. 41(3), 369–382 (1996).
[Crossref] [PubMed]

Herz, P.

Huffman, D.

C. Bohren and D. Huffman, Absorption and Scattering of Light by Small Particles, Wiley Science Paperback Series (John Wiley and Sons, New York, 1998).

Insana, M. F.

P. Chaturvedi and M. F. Insana, “Autoregressive spectral estimation in ultrasonic scatterer size imaging,” Ultrason. Imaging 18(1), 10–24 (1996).
[Crossref] [PubMed]

Ippen, E. P.

U. Morgner, W. Drexler, F. X. Kärtner, X. D. Li, C. Pitris, E. P. Ippen, and J. G. Fujimoto, “Spectroscopic optical coherence tomography,” Opt. Lett. 25(2), 111–113 (2000).
[Crossref]

Isenberg, G.

Itzkan, I.

Izatt, J. A.

A. Wax, C. Yang, and J. A. Izatt, “Fourier-domain low-coherence interferometry for light-scattering spectroscopy,” Opt. Lett. 28(14), 1230–1232 (2003).
[Crossref] [PubMed]

Jolliffe, I. T.

I. T. Jolliffe, Principal Component Analysis, 2nd ed. (Springer-Verlag, 2002).

Kabani, S.

Kalashnikov, M.

Kamalabadi, F.

Kamensky, V. A.

Kartakoullis, A.

C. Pitris, A. Kartakoullis, and E. Bousi, “AM-FM techniques in the analysis of optical coherence tomography signals,” J. Biophoton. 2(6–7), 364–369 (2009).
[Crossref]

Kärtner, F. X.

U. Morgner, W. Drexler, F. X. Kärtner, X. D. Li, C. Pitris, E. P. Ippen, and J. G. Fujimoto, “Spectroscopic optical coherence tomography,” Opt. Lett. 25(2), 111–113 (2000).
[Crossref]

Kline, E.

Ko, T.

Levin, H. S.

Li, X. D.

U. Morgner, W. Drexler, F. X. Kärtner, X. D. Li, C. Pitris, E. P. Ippen, and J. G. Fujimoto, “Spectroscopic optical coherence tomography,” Opt. Lett. 25(2), 111–113 (2000).
[Crossref]

Lima, C.

Lingley-Papadopoulos, C. A.

Loew, M. H.

MacQueen, J. B.

J. B. MacQueen, “Some Methods for classification and Analysis of Multivariate Observations,” Proceedings of 5-th Berkeley Symposium on Mathematical Statistics and Probability, University of California Press1, 281–297 (1967).

Manoharan, R.

Manolakis, D.

J. Proakis and D. Manolakis, Digital Signal Processing, Principles, Algorithms and Applications (Prentice Hall, 2006).

Manyak, M. J.

Marks, D. L.

McGillican, T.

Mik, E. G.

Minet, O.

J. Beuthan, O. Minet, J. Helfmann, M. Herrig, and G. Müller, “The spatial variation of the refractive index in biological cells,” Phys. Med. Biol. 41(3), 369–382 (1996).
[Crossref] [PubMed]

Morgner, U.

U. Morgner, W. Drexler, F. X. Kärtner, X. D. Li, C. Pitris, E. P. Ippen, and J. G. Fujimoto, “Spectroscopic optical coherence tomography,” Opt. Lett. 25(2), 111–113 (2000).
[Crossref]

Moses, R. L.

P. Stoica and R. L. Moses, Introduction to Spectral Analysis (Prentice Hall, 1997).

Mueller, M.

Müller, G.

J. Beuthan, O. Minet, J. Helfmann, M. Herrig, and G. Müller, “The spatial variation of the refractive index in biological cells,” Phys. Med. Biol. 41(3), 369–382 (1996).
[Crossref] [PubMed]

Müller, M. G.

Nusrat, A.

Perelman, L.

Perelman, L. T.

Pitris, C.

C. Pitris, A. Kartakoullis, and E. Bousi, “AM-FM techniques in the analysis of optical coherence tomography signals,” J. Biophoton. 2(6–7), 364–369 (2009).
[Crossref]

U. Morgner, W. Drexler, F. X. Kärtner, X. D. Li, C. Pitris, E. P. Ippen, and J. G. Fujimoto, “Spectroscopic optical coherence tomography,” Opt. Lett. 25(2), 111–113 (2000).
[Crossref]

Povazay, B.

Proakis, J.

J. Proakis and D. Manolakis, Digital Signal Processing, Principles, Algorithms and Applications (Prentice Hall, 2006).

Qi, X.

Richards-Kortum, R.

A. Dunn and R. Richards-Kortum, “Three-dimensional computation of light scattering from cells,” IEEE J. Sel. Top. Quantum Electron. 2(4), 898–905 (1996).
[Crossref]

Rollins, A. M.

Sattmann, H.

Schmetterer, L.

Seiler, M.

Sergeeva, E. A.

Shakhova, N. M.

Shapshay, S.

Shields, S.

Shields, S. J.

Sivak, M. V.

Stephens, D. J.

D. J. Stephens and V. J. Allan, “Light microscopy techniques for live cell imaging,” Science 300(5616), 82–86 (2003).
[Crossref] [PubMed]

Stoica, P.

P. Stoica and R. L. Moses, Introduction to Spectral Analysis (Prentice Hall, 1997).

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Fig. 1. Back-scattered Mie spectra for (a) 1 μm, (b) 2 μm, and (c) 4 μm scatterer corresponding to the wavelength range of the source used in the experimental section.

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Fig. 2. (a) Back-scattered normalized average autocorrelation obtained with FFT. (b) Back-scattered normalized average power spectra obtained with Burg’s method

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Fig. 3. Classification results from linear discriminant analysis and k-means clustering of OCT images of polystyrene microspheres embedded in an acrylamide gel. (a) OCT intensity image of three regions with different size spheres. (b) The results of classification of (a) using Burg’s algorithm and linear discriminant analysis. (c) The results of classification of (a) using Burg’s algorithm and k-means clustering. (d) OCT intensity image of three regions with different size spheres. (e) The results of classification of (d) using FFT and linear discriminant analysis. (f) The results of classification of (d) using FFT and k-means clustering. Image size: 1 × 3 mm

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Fig. 4. (a) Ex-vivo demodulated amplitude OCT image from k-means clustering of OCT images of neuronal tissue containing a blood vessel (v), a nerve (n) and fatty tissue (f). (b) Pseudo color image of the clustering results of the spectral data of the OCT image. Large and small fascicles in the neuron are indicated by arrows. Image size: 1.5 × 1.95 mm

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Tables (3)

Table 1. Scattering Cross-Sections of the Phantoms and Cellular Structures at 1.255 μm wavelength.

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Table 2. Diameter estimation results for Burg’s Method and for FFT/Autocorrelation

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Table 3. Results for Burg’s Method and FFT classification and k-means clustering.

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Equations (16)

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γ_{xx} (τ) = E {x^{*} (t) x (t + τ)}

r_{xx} = \frac{1}{N} \sum_{n = 0}^{N - m - 1} x^{*} (n) x (n + m) 0 \leq m \leq N - 1

= \frac{1}{N} \sum_{n = ∣ m ∣}^{N - 1} x^{*} (n) x (n + m) m = - 1, - 2, \dots, 1 - N

P_{xx} (ω) = \sum_{m = - (N - 1)}^{N - 1} r_{xx} (m) \exp (- jωm)

P_{xx} (ω) = \frac{1}{N} ∣ \sum_{n = 0}^{N - 1} x (n) \exp {(- jωm) ∣}^{2} = \frac{1}{N} {| X (ω) ∣}^{2}

x (n) + \sum_{k = 1}^{p} α_{k} x (n - k) = w (n)

P_{xx}^{AR} (ω) = \frac{{| b_{0} ∣}^{2}}{{| A (ω) ∣}^{2}}

P_{xx}^{AR} (ω) = \frac{σ_{p}^{2}}{{| A (ω) ∣}^{2}}

{\hat{α}}_{p, k} = {\begin{matrix} {\hat{α}}_{p - 1, k} + {\hat{k}}_{p} {\hat{α}}_{p - 1, p - i,}^{*} i = 1, \dots, p - 1 \\ {\hat{k}}_{p}, i = p \end{matrix}

{\hat{P}}_{xx}^{Bu} (ω) = \frac{{\hat{σ}}_{P}^{2}}{{| 1 + \sum_{k = 1}^{p} {\hat{α}}_{p} (k) \exp (- jωk) |}^{2}}

FV = ({PC}_{1} {PC}_{2} \dots {PC}_{n})

{\hat{P}}_{xx}^{{PCA}_{sa}} = P_{xx}^{sa} FV

{\hat{P}}_{xx}^{{PCA}_{tr}} = P_{xx}^{tr} FV

\hat{A} = {\hat{P}}_{xx}^{{PCA}_{tr}^{- 1}} d_{tr}

d_{sample} = {\hat{P}}_{sa}^{PCA} \hat{A}

V = \sum_{j = 1}^{k} \sum_{i = 1}^{n} {∥ x_{i}^{(j)} - c_{j} ∥}^{2}

Structure	Scattering Cross-Section (μm²)	Index of Refraction of Medium	Index of Refraction of Scatterer	Diameter (μm)
1μm Phantom	0.12906	1.47	1.59	1
2μm Phantom	2.1668	1.47	1.59	2
4μ Phantom	27.959	1.47	1.59	4

Mitochondria	0.021429	1.37	1.42	1
Nucleus	0.99678	1.37	1.39	4
Cell	37.669	1.35	1.37	10

	Burg’s Method			FFT/Autocorrelation
Scatterer Diameter From Manufacturer (μm)	1±0.03	2±0.10	4±0.28	1±0.03	2±0.10	4±0.28
Mean Estimated Diameter (μm)	1.00	2.08	3.93	1.09	2.05	3.64
Standard Deviation (μm)	0.324	0.528	0.540	0.980	1.092	1.124

Diameter (μm)	Burg’s Method & Discriminant Analysis		FFT & Discriminant Analysis		Burg’s Method & k-Means Clustering		FFT & k-Means Clustering
	Sensitivity (%)	Specificity (%)	Sensitivity (%)	Sensitivity (%)	Specificity (%)	Specificity (%)	Sensitivity (%)	Specificity (%)
1	95.0	99.5	81.4	93.1	95.1	99.4	67.6	81.1
2	90.4	99.5	76.7	93.1	97.1	99.4	63.7	89.1
4	93.4	99.5	87.2	93.1	93.6	99.4	66.1	78.4

Structure	Scattering Cross-Section (μm²)	Index of Refraction of Medium	Index of Refraction of Scatterer	Diameter (μm)
1μm Phantom	0.12906	1.47	1.59	1
2μm Phantom	2.1668	1.47	1.59	2
4μ Phantom	27.959	1.47	1.59	4

Mitochondria	0.021429	1.37	1.42	1
Nucleus	0.99678	1.37	1.39	4
Cell	37.669	1.35	1.37	10

	Burg’s Method			FFT/Autocorrelation
Scatterer Diameter From Manufacturer (μm)	1±0.03	2±0.10	4±0.28	1±0.03	2±0.10	4±0.28
Mean Estimated Diameter (μm)	1.00	2.08	3.93	1.09	2.05	3.64
Standard Deviation (μm)	0.324	0.528	0.540	0.980	1.092	1.124