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Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 19, Iss. 8 — Apr. 11, 2011
  • pp: 7559–7566
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Defect detection and property evaluation of indium tin oxide conducting glass using optical coherence tomography

Meng-Tsan Tsai, Feng-Yu Chang, Ya-Ju Lee, Jiann-Der Lee, Hsiang-Chen Wang, and Cheng-Kuang Lee  »View Author Affiliations


Optics Express, Vol. 19, Issue 8, pp. 7559-7566 (2011)
http://dx.doi.org/10.1364/OE.19.007559


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Abstract

This study demonstrates a new approach for evaluating the properties of indium tin oxide (ITO) conducting glass and identifying defects using optical coherence tomography (OCT). A swept-source OCT system was implemented to scan the ITO conducting glass to enable two-dimensional or three-dimensional imaging. With OCT scanning, the defects can be clearly identified at various depths. Several parameters in addition to morphological information can be estimated simultaneously, including the thickness of the glass substrate, the refractive index, reflection coefficient, and transmission coefficient, all of which can be used to evaluate the quality of ITO conducting glass. This study developed a modified method for evaluating the refractive index of glass substrates without having to perform multiple scans as well as a segmentation algorithm to separate the interfaces. The results show the potential of OCT as an imaging tool for the inspection of defects in ITO conducting glass.

© 2011 OSA

1. Introduction

2. System setup and OCT scan

Figure 1
Fig. 1 Schematic diagram of the SS-OCT system used for scanning ITO conducting glass. SS: swept-source, PC: optical polarization controller, CIR: optical circulator.
shows the schematic diagram of the OCT system. A frequency-sweeping laser centered at 1.3 μm with a FWHM of 100 nm was operated at the sweeping rate of 30 kHz. The frequency-sweeping laser can provide 6 mW of output power and was connected to a Mach-Zehnder interferometer consisting of two couplers and two circulators. In the reference arm, a neutral density (ND) filter was inserted to maximize system sensitivity. In the sample arm, a pair of scanning galvanometers were implemented to provide the optical beam translation in X and Y dimensions. The interference fringe signal was then detected by a balanced photodetector (PDB150C, Thorlabs) and sampled by a high-speed digitizer (PXI-5122, National Instrument). With the sweeping rate of 30 kHz, the system could achieve a frame rate of 30 frames/s, each frame consisting of 1000 A-mode scans. In the three-dimensional (3D) data acquisition, the whole data could be acquired in 2 sec, each consisting of 600 x 300 x 200 voxels and spanning a range of 4 mm x 3 mm x 3 mm. System sensitivity can reach 105 dB. The system dispersion is compensated by a software compensation scheme [23

23. Y. Yasuno, V. D. Madjarova, S. Makita, M. Akiba, A. Morosawa, C. Chong, T. Sakai, K. P. Chan, M. Itoh, and T. Yatagai, “Three-dimensional and high-speed swept-source optical coherence tomography for in vivo investigation of human anterior eye segments,” Opt. Express 13(26), 10652–10664 (2005). [CrossRef] [PubMed]

]. In our OCT system, the longitudinal and transverse resolutions are approximately 8 μm and 15 μm, respectively.

Before OCT scanning, a reflective mirror is placed on a precision stage, and a piece of defective ITO conducting glass is placed on the reflective mirror with perfect contact in the sample arm. 3D OCT imaging was performed on ITO conducting glass and Fig. 2
Fig. 2 Images of ITO conducting glass. (a) 3D OCT image of defective ITO conducting glass, (b) an en-face image of the top surface extracted from (a), (c) an en-face image of the bottom surface extracted from (a), and (d) image of normal ITO conducting glass obtained using a Microscope with a 10x objective lens. The scale bar in the figure represents 1 mm.
shows the OCT scanning results. Figure 2(a) represents a 3D OCT image with a volume size of 600 x 300 x 200 voxels. Figures 2(b) and 2(c) show the en-face images of the top and bottom surfaces extracted from the 3D OCT image, illustrating the defect distribution along the depth range, which is difficult to be obtained from the machine vision technique. Figure 2(d) represents the surface image of a normal ITO conducting glass examined by a microscope with a 10x objective lens. Compared with microscopic results, the same features can be found from the OCT images. Based on the OCT images, the defects in micron scale can be clearly identified.

3. Principle for the estimation of group refractive index

Although OCT images are useful for identifying defects in ITO conducting glass, optical properties are also important for quantitatively evaluating its quality. These optical properties include homogeneity, the thickness of the substrate, and transmission efficiency. The group refractive index can be used as an accurate indicator of the homogeneity of a glass substrate. Several methods have been proposed to calculate the refractive index of biological tissue or optical components [24

24. G. J. Tearney, M. E. Brezinski, J. F. Southern, B. E. Bouma, M. R. Hee, and J. G. Fujimoto, “Determination of the refractive index of highly scattering human tissue by optical coherence tomography,” Opt. Lett. 20(21), 2258–2260 (1995). [CrossRef] [PubMed]

28

28. S. Kim, J. Na, M. J. Kim, and B. H. Lee, “Simultaneous measurement of refractive index and thickness by combining low-coherence interferometry and confocal optics,” Opt. Express 16(8), 5516–5526 (2008). [CrossRef] [PubMed]

]; however, it has been difficult to obtain the refractive index using the same measurements and it has been necessary to accurately control the depth of field in the sample arm. Kim et al. [28

28. S. Kim, J. Na, M. J. Kim, and B. H. Lee, “Simultaneous measurement of refractive index and thickness by combining low-coherence interferometry and confocal optics,” Opt. Express 16(8), 5516–5526 (2008). [CrossRef] [PubMed]

] demonstrated a novel concept to determine the refractive index by moving the positions of the mirror in the reference arm and the objective lens in the reference arm; however, the refractive index was difficult to obtain in a single measurement. In this study, we modified this concept to obtain a group refractive index simultaneously, without having to adjust for the difference in the optical path between the reference and sample arms.

4. Segmentation algorithm and properties evaluation

In this study, the glass substrate was placed to face the incident light and on the other side of ITO conducting glass, the ITO film directly contacted the reflective mirror. To estimate accurately the refractive index of glass substrate, a segmentation algorithm was developed to discriminate the different interfaces including the first plane of glass substrate, secondary plane of glass substrate, and the reflective mirror. Figure 4
Fig. 4 Flow diagram of segmentation algorithm and data process for properties evaluation.
shows the flow diagram of the data process. At the beginning of the flow diagram, the two peaks can be found in each A-scan profile of ITO conducting glass placed on the reflective mirror, corresponding to the first plane of the glass substrate and secondary plane of the glass substrate, respectively. Conversely, the maximum peak of each A-scan profile obtained from the reflective mirror represents the initial position of reflective mirror. Hence, OPDG can be acquired to calculate the difference between the first and second peaks. OSM can be obtained by calculating the difference between the second peak of A-scan profiles of ITO conducting glass placed on the reflective mirror and the maximum peak of A-mode scan profiles of the reflective mirror, as shown in Fig. 4. According to Eq. (1) and Eq. (2), several parameters can be evaluated simultaneously including the refractive index, thickness of glass substrate, reflection coefficient, and transmission coefficient.

Based on the segmentation algorithm, the refractive index distribution of Fig. 2(a) could be obtained, as shown in Fig. 5(a)
Fig. 5 (a) Refractive index distribution of ITO conducting glass evaluated from 3D OCT data of Fig. 2(a). (b) Thickness distribution of glass substrate evaluated from 3D OCT data of Fig. 2(a).
. The mean value of refractive index is demonstrated in Fig. 5(a) to give approximately 1.5312 and the standard deviation of the refractive index in Fig. 5(a) is also evaluated to give 0.0559. From the result, one can see that the smaller values of refractive indices in Fig. 5(a) correspond to the locations of defects in Fig. 2(a). The larger standard deviation compared with that of BK7 material results from the existence of defect. Hence, the evaluation of the refractive index of ITO conducting glass can also be useful for inspecting the quality of ITO conducting glass. With the estimated refractive indices, the thickness distribution of glass substrate can also be determined from Eq. (1). Figure 5(b) represents the thickness distribution of the glass substrate evaluated from the same 3D OCT data of Fig. 2(a). The mean value of thickness is demonstrated in Fig. 5(b) to give approximately 658.1 μm, and the standard deviation of the thickness in Fig. 5(b) is also evaluated to give 5.2 μm. Due to the uniformity of transmission efficiency being associated with the uniformity of thickness, the thickness can also be used as an accurate indicator for evaluating the quality. In addition, the reflection and transmission coefficients of glass substrate can be acquired using Eq. (3).
R=(n1n+1)2andT=4n(n+1)2
(3)
where R and T denote the reflection and transmission coefficients, respectively. Since the extinction coefficient of glass substrate is extremely small for the detecting light (κ = 2.5 × 10−7 at λ = 1.3 μm for BK7 material), it is reasonable to assume the sum of R and T is equal to 1. The distributions of reflection and transmission coefficients are shown in Figs. 6(a)
Fig. 6 Distributions of reflection coefficient (a) and transmission coefficient (b) evaluated from 3D OCT data of Fig. 2(a).
and 6(b), respectively. Here, the mean values of Figs. 6(a) and 6(b) are also estimated to give 0.9559 and 0.0441, respectively, and each of the standard deviations in Figs. 6(a) and 6(b) is equal to 0.0054. Here, one can see that the reflection and transmission coefficients can also be accurate indicators for property evaluation of ITO conducting glass.

In this paper, we propose a modified method to evaluate the refractive index. This method is only suitable to be used for the transparent samples for acquiring the position of the reflective mirror; therefore, evaluating the refractive index of the opaque samples is difficult. In this paper, we show only the results of the ITO film contacting the reflective mirror. However, the segmentation algorithm and data process for property evaluation can also be used when the ITO film is faced toward the incident light.

5. Conclusions

To summarize, we demonstrate a new approach for defect inspection and property evaluation of ITO conducting glass using OCT. The machine vision technique is the most common method used for defect detection for ITO conducting glass, but can only provide surface images without depth information causing difficulty identifying the defects below the glass surface. Compared with the machine vision technique, OCT can reconstruct the three-dimensional microstructure of a sample at a depth range of 2-3 mm. Using OCT scanning, the defects can be clearly identified at various depths. Several parameters in addition to morphological information can be estimated simultaneously, including the thickness of the glass substrate, the refractive index, reflection coefficient, and transmission coefficient, all of which can be used to evaluate the quality of ITO conducting glass. In this study, a modified method is proposed to evaluate the refractive index of glass substrates without multiple scans; and a segmentation algorithm to separate the different interfaces is also developed. From the results, one can see that OCT could be a potential imaging tool for defect inspection of ITO conducting glass or other industrial products such as flexible printed circuit boards, blue-ray discs, and OLED displays.

Acknowledgement

This research was supported by National Science Council, the Republic of China, under the grants of NSC 99–2221–E–182–044 and NSC–98–2112–M–003–001–MY2, and also by Chang Gung University, the Republic of China, under the grant of UERPD290011.

References and links

1.

J. Manifacier, “Thin metallic oxides as transparent conductors,” Thin Solid Films 90(3), 297–308 (1982). [CrossRef]

2.

O. Yavas and M. Takai, “High-speed maskless laser patterning of indium tin oxide thin films,” Appl. Phys. Lett. 73(18), 2558–2560 (1998). [CrossRef]

3.

B.-S. Chiou and J.-H. Tsai, “B. S. Chiou, J. H. Tsai, “Antireflection coating for ITO films deposited on glass substrate,” J. Mater. Sci. Mater. Electron. 10(7), 491–495 (1999). [CrossRef]

4.

C. Steger, M. Ulrich, and C. Wiedemann, Machine vision algorithm and applications (Weinheim: Wiley-VCH, 2008).

5.

T. Kido, N. Kishi, and H. Takahashi, “Optical charge-sensing method for testing and characterizing thin-film transistor arrays,” IEEE J. Sel. Top. Quantum Electron. 1(4), 993–1001 (1995). [CrossRef]

6.

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 et, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991). [CrossRef] [PubMed]

7.

S. Yun, G. Tearney, B. Bouma, B. Park, and J. de Boer, “High-speed spectral-domain optical coherence tomography at 1.3 mum wavelength,” Opt. Express 11(26), 3598–3604 (2003). [CrossRef] [PubMed]

8.

M. Wojtkowski, V. Srinivasan, T. Ko, J. Fujimoto, A. Kowalczyk, and J. Duker, “Ultrahigh-resolution, high-speed, Fourier domain optical coherence tomography and methods for dispersion compensation,” Opt. Express 12(11), 2404–2422 (2004). [CrossRef] [PubMed]

9.

B. Cense, N. Nassif, T. Chen, M. Pierce, S. H. Yun, B. Park, B. Bouma, G. Tearney, and J. de Boer, “Ultrahigh-resolution high-speed retinal imaging using spectral-domain optical coherence tomography,” Opt. Express 12(11), 2435–2447 (2004). [CrossRef] [PubMed]

10.

J. F. de Boer, “Spectral/Fourier domain optical coherence tomography,” in Optical Coherence Tomography, Technology and Applications, Wolfgang Drexler, and James G. Fujimoto, eds. (Springer, 2008), pp. 147–175.

11.

S. Yun, G. Tearney, J. de Boer, N. Iftimia, and B. Bouma, “High-speed optical frequency-domain imaging,” Opt. Express 11(22), 2953–2963 (2003). [CrossRef] [PubMed]

12.

Y. Yasuno, Y. Hong, S. Makita, M. Yamanari, M. Akiba, M. Miura, and T. Yatagai, “In vivo high-contrast imaging of deep posterior eye by 1-μm swept source optical coherence tomography and scattering optical coherence angiography,” Opt. Express 15(10), 6121–6139 (2007). [CrossRef] [PubMed]

13.

R. Huber, D. C. Adler, and J. G. Fujimoto, “Buffered Fourier domain mode locking: Unidirectional swept laser sources for optical coherence tomography imaging at 370,000 lines/s,” Opt. Lett. 31(20), 2975–2977 (2006). [CrossRef] [PubMed]

14.

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]

15.

M. Choma, M. Sarunic, C. Yang, and J. Izatt, “Sensitivity advantage of swept source and Fourier domain optical coherence tomography,” Opt. Express 11(18), 2183–2189 (2003). [CrossRef] [PubMed]

16.

D. C. Adler, Y. Chen, R. Huber, J. Schmitt, J. Connolly, and J. G. Fujimoto, “Three-dimensional endomicroscopy using optical coherence tomography,” Nat. Photonics 1, 709–716 (2007).

17.

Y. Hori, Y. Yasuno, S. Sakai, M. Matsumoto, T. Sugawara, V. Madjarova, M. Yamanari, S. Makita, T. Yasui, T. Araki, M. Itoh, and T. Yatagai, “Automatic characterization and segmentation of human skin using three-dimensional optical coherence tomography,” Opt. Express 14(5), 1862–1877 (2006). [CrossRef] [PubMed]

18.

M. T. Tsai, H. C. Lee, C. K. Lee, C. H. Yu, H. M. Chen, C. P. Chiang, C. C. Chang, Y. M. Wang, and C. C. Yang, “Effective indicators for diagnosis of oral cancer using optical coherence tomography,” Opt. Express 16(20), 15847–15862 (2008). [CrossRef] [PubMed]

19.

X. Qi, Y. Pan, M. V. Sivak, J. E. Willis, G. Isenberg, and A. M. Rollins, “Image analysis for classification of dysplasia in Barrett’s esophagus using endoscopic optical coherence tomography,” Biomed. Opt. Express 1(3), 825–847 (2010). [CrossRef]

20.

G. J. Tearney, H. Yabushita, S. L. Houser, H. T. Aretz, I. K. Jang, K. H. Schlendorf, C. R. Kauffman, M. Shishkov, E. F. Halpern, and B. E. Bouma, “Quantification of macrophage content in atherosclerotic plaques by optical coherence tomography,” Circulation 107(1), 113–119 (2003). [CrossRef] [PubMed]

21.

C. W. Lu, I. J. Hsu, H. C. Wang, M. T. Tsai, C. C. Yang, and M. L. Yang, “Application of optical coherence tomography to monitoring the subsurface morphology of archaic jades,” IEEE, Taipei, Taiwan 301, 308 (2003).

22.

D. C. Adler, J. Stenger, I. Gorczynska, H. Lie, T. Hensick, R. Spronk, S. Wolohojian, N. Khandekar, J. Y. Jiang, S. Barry, A. E. Cable, R. Huber, and J. G. Fujimoto, “Comparison of three-dimensional optical coherence tomography and high resolution photography for art conservation studies,” Opt. Express 15(24), 15972–15986 (2007). [CrossRef] [PubMed]

23.

Y. Yasuno, V. D. Madjarova, S. Makita, M. Akiba, A. Morosawa, C. Chong, T. Sakai, K. P. Chan, M. Itoh, and T. Yatagai, “Three-dimensional and high-speed swept-source optical coherence tomography for in vivo investigation of human anterior eye segments,” Opt. Express 13(26), 10652–10664 (2005). [CrossRef] [PubMed]

24.

G. J. Tearney, M. E. Brezinski, J. F. Southern, B. E. Bouma, M. R. Hee, and J. G. Fujimoto, “Determination of the refractive index of highly scattering human tissue by optical coherence tomography,” Opt. Lett. 20(21), 2258–2260 (1995). [CrossRef] [PubMed]

25.

M. Haruna, M. Ohmi, T. Mitsuyama, H. Tajiri, H. Maruyama, and M. Hashimoto, “Simultaneous measurement of the phase and group indices and the thickness of transparent plates by low-coherence interferometry,” Opt. Lett. 23(12), 966–968 (1998). [CrossRef]

26.

A. Hirai and H. Matsumoto, “Low-coherence tandem interferometer for measurement of group refractive index without knowledge of the thickness of the test sample,” Opt. Lett. 28(21), 2112–2114 (2003). [CrossRef] [PubMed]

27.

Y. S. Ghim and S. W. Kim, “Thin-film thickness profile and its refractive index measurements by dispersive white-light interferometry,” Opt. Express 14(24), 11885–11891 (2006). [CrossRef] [PubMed]

28.

S. Kim, J. Na, M. J. Kim, and B. H. Lee, “Simultaneous measurement of refractive index and thickness by combining low-coherence interferometry and confocal optics,” Opt. Express 16(8), 5516–5526 (2008). [CrossRef] [PubMed]

29.

“Refractive index database,” http://Refractiveindex.info

OCIS Codes
(110.4500) Imaging systems : Optical coherence tomography
(120.0120) Instrumentation, measurement, and metrology : Instrumentation, measurement, and metrology
(120.3180) Instrumentation, measurement, and metrology : Interferometry
(120.4630) Instrumentation, measurement, and metrology : Optical inspection

ToC Category:
Instrumentation, Measurement, and Metrology

History
Original Manuscript: December 22, 2010
Revised Manuscript: March 4, 2011
Manuscript Accepted: March 28, 2011
Published: April 5, 2011

Citation
Meng-Tsan Tsai, Feng-Yu Chang, Ya-Ju Lee, Jiann-Der Lee, Hsiang-Chen Wang, and Cheng-Kuang Lee, "Defect detection and property evaluation of indium tin oxide conducting glass using optical coherence tomography," Opt. Express 19, 7559-7566 (2011)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-19-8-7559


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References

  1. J. Manifacier, “Thin metallic oxides as transparent conductors,” Thin Solid Films 90(3), 297–308 (1982). [CrossRef]
  2. O. Yavas and M. Takai, “High-speed maskless laser patterning of indium tin oxide thin films,” Appl. Phys. Lett. 73(18), 2558–2560 (1998). [CrossRef]
  3. B.-S. Chiou and J.-H. Tsai, “B. S. Chiou, J. H. Tsai, “Antireflection coating for ITO films deposited on glass substrate,” J. Mater. Sci. Mater. Electron. 10(7), 491–495 (1999). [CrossRef]
  4. C. Steger, M. Ulrich, and C. Wiedemann, Machine vision algorithm and applications (Weinheim: Wiley-VCH, 2008).
  5. T. Kido, N. Kishi, and H. Takahashi, “Optical charge-sensing method for testing and characterizing thin-film transistor arrays,” IEEE J. Sel. Top. Quantum Electron. 1(4), 993–1001 (1995). [CrossRef]
  6. 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 et, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991). [CrossRef] [PubMed]
  7. S. Yun, G. Tearney, B. Bouma, B. Park, and J. de Boer, “High-speed spectral-domain optical coherence tomography at 1.3 mum wavelength,” Opt. Express 11(26), 3598–3604 (2003). [CrossRef] [PubMed]
  8. M. Wojtkowski, V. Srinivasan, T. Ko, J. Fujimoto, A. Kowalczyk, and J. Duker, “Ultrahigh-resolution, high-speed, Fourier domain optical coherence tomography and methods for dispersion compensation,” Opt. Express 12(11), 2404–2422 (2004). [CrossRef] [PubMed]
  9. B. Cense, N. Nassif, T. Chen, M. Pierce, S. H. Yun, B. Park, B. Bouma, G. Tearney, and J. de Boer, “Ultrahigh-resolution high-speed retinal imaging using spectral-domain optical coherence tomography,” Opt. Express 12(11), 2435–2447 (2004). [CrossRef] [PubMed]
  10. J. F. de Boer, “Spectral/Fourier domain optical coherence tomography,” in Optical Coherence Tomography, Technology and Applications, Wolfgang Drexler, and James G. Fujimoto, eds. (Springer, 2008), pp. 147–175.
  11. S. Yun, G. Tearney, J. de Boer, N. Iftimia, and B. Bouma, “High-speed optical frequency-domain imaging,” Opt. Express 11(22), 2953–2963 (2003). [CrossRef] [PubMed]
  12. Y. Yasuno, Y. Hong, S. Makita, M. Yamanari, M. Akiba, M. Miura, and T. Yatagai, “In vivo high-contrast imaging of deep posterior eye by 1-μm swept source optical coherence tomography and scattering optical coherence angiography,” Opt. Express 15(10), 6121–6139 (2007). [CrossRef] [PubMed]
  13. R. Huber, D. C. Adler, and J. G. Fujimoto, “Buffered Fourier domain mode locking: Unidirectional swept laser sources for optical coherence tomography imaging at 370,000 lines/s,” Opt. Lett. 31(20), 2975–2977 (2006). [CrossRef] [PubMed]
  14. 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]
  15. M. Choma, M. Sarunic, C. Yang, and J. Izatt, “Sensitivity advantage of swept source and Fourier domain optical coherence tomography,” Opt. Express 11(18), 2183–2189 (2003). [CrossRef] [PubMed]
  16. D. C. Adler, Y. Chen, R. Huber, J. Schmitt, J. Connolly, and J. G. Fujimoto, “Three-dimensional endomicroscopy using optical coherence tomography,” Nat. Photonics 1, 709–716 (2007).
  17. Y. Hori, Y. Yasuno, S. Sakai, M. Matsumoto, T. Sugawara, V. Madjarova, M. Yamanari, S. Makita, T. Yasui, T. Araki, M. Itoh, and T. Yatagai, “Automatic characterization and segmentation of human skin using three-dimensional optical coherence tomography,” Opt. Express 14(5), 1862–1877 (2006). [CrossRef] [PubMed]
  18. M. T. Tsai, H. C. Lee, C. K. Lee, C. H. Yu, H. M. Chen, C. P. Chiang, C. C. Chang, Y. M. Wang, and C. C. Yang, “Effective indicators for diagnosis of oral cancer using optical coherence tomography,” Opt. Express 16(20), 15847–15862 (2008). [CrossRef] [PubMed]
  19. X. Qi, Y. Pan, M. V. Sivak, J. E. Willis, G. Isenberg, and A. M. Rollins, “Image analysis for classification of dysplasia in Barrett’s esophagus using endoscopic optical coherence tomography,” Biomed. Opt. Express 1(3), 825–847 (2010). [CrossRef]
  20. G. J. Tearney, H. Yabushita, S. L. Houser, H. T. Aretz, I. K. Jang, K. H. Schlendorf, C. R. Kauffman, M. Shishkov, E. F. Halpern, and B. E. Bouma, “Quantification of macrophage content in atherosclerotic plaques by optical coherence tomography,” Circulation 107(1), 113–119 (2003). [CrossRef] [PubMed]
  21. C. W. Lu, I. J. Hsu, H. C. Wang, M. T. Tsai, C. C. Yang, and M. L. Yang, “Application of optical coherence tomography to monitoring the subsurface morphology of archaic jades,” IEEE, Taipei, Taiwan 301, 308 (2003).
  22. D. C. Adler, J. Stenger, I. Gorczynska, H. Lie, T. Hensick, R. Spronk, S. Wolohojian, N. Khandekar, J. Y. Jiang, S. Barry, A. E. Cable, R. Huber, and J. G. Fujimoto, “Comparison of three-dimensional optical coherence tomography and high resolution photography for art conservation studies,” Opt. Express 15(24), 15972–15986 (2007). [CrossRef] [PubMed]
  23. Y. Yasuno, V. D. Madjarova, S. Makita, M. Akiba, A. Morosawa, C. Chong, T. Sakai, K. P. Chan, M. Itoh, and T. Yatagai, “Three-dimensional and high-speed swept-source optical coherence tomography for in vivo investigation of human anterior eye segments,” Opt. Express 13(26), 10652–10664 (2005). [CrossRef] [PubMed]
  24. G. J. Tearney, M. E. Brezinski, J. F. Southern, B. E. Bouma, M. R. Hee, and J. G. Fujimoto, “Determination of the refractive index of highly scattering human tissue by optical coherence tomography,” Opt. Lett. 20(21), 2258–2260 (1995). [CrossRef] [PubMed]
  25. M. Haruna, M. Ohmi, T. Mitsuyama, H. Tajiri, H. Maruyama, and M. Hashimoto, “Simultaneous measurement of the phase and group indices and the thickness of transparent plates by low-coherence interferometry,” Opt. Lett. 23(12), 966–968 (1998). [CrossRef]
  26. A. Hirai and H. Matsumoto, “Low-coherence tandem interferometer for measurement of group refractive index without knowledge of the thickness of the test sample,” Opt. Lett. 28(21), 2112–2114 (2003). [CrossRef] [PubMed]
  27. Y. S. Ghim and S. W. Kim, “Thin-film thickness profile and its refractive index measurements by dispersive white-light interferometry,” Opt. Express 14(24), 11885–11891 (2006). [CrossRef] [PubMed]
  28. S. Kim, J. Na, M. J. Kim, and B. H. Lee, “Simultaneous measurement of refractive index and thickness by combining low-coherence interferometry and confocal optics,” Opt. Express 16(8), 5516–5526 (2008). [CrossRef] [PubMed]
  29. “Refractive index database,” http://Refractiveindex.info

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