Abstract

We propose methods to align interferograms affected by trigger jitter to a reference interferogram based on the information (amplitude/phase) at a fixed-pattern noise location to reduce residual fixed-pattern noise and improve the phase stability of swept source optical coherence tomography (SS-OCT) systems. One proposed method achieved this by introducing a wavenumber shift (k-shift) in the interferograms of interest and searching for the k-shift that minimized the fixed-pattern noise amplitude. The other method calculated the relative k-shift using the phase information at the residual fixed-pattern noise location. Repeating this wavenumber alignment procedure for all A-lines of interest produced fixed-pattern noise free and phase stable OCT images. A system incorporating these correction routines was used for human retina OCT and Doppler OCT imaging. The results from the two methods were compared, and it was found that the intensity-based method provided better results.

© 2015 Optical Society of America

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References

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2013 (2)

2012 (1)

2011 (4)

2007 (1)

2005 (1)

2004 (1)

Adler, D. C.

Baumann, B.

Bouma, B.

Braaf, B.

Cable, A. E.

Chen, Z.

Choi, W.

de Boer, J.

de Boer, J. F.

Dhalla, A.-H.

Duker, J. S.

Foulad, A.

Fujimoto, J. G.

Grulkowski, I.

Hendargo, H. C.

Hong, Y.-J.

Hornegger, J.

Huang, D.

Huber, R.

Itoh, M.

Izatt, J. A.

Jaillon, F.

Jayaraman, V.

Ju, M. J.

Kampik, A.

Klein, T.

Kraus, M. F.

Lee, B. H.

Liu, G.

Liu, J. J.

Lu, C. D.

Makita, S.

McNabb, R. P.

Min, E. J.

Miura, M.

Neubauer, A.

Potsaid, B.

Qi, W.

Reznicek, L.

Rubinstein, M.

Saidi, A.

Shepherd, N.

Sicam, V. A. D. P.

Tearney, G.

Vakoc, B.

van Meurs, J. C.

van Zeeburg, E.

Vermeer, K. A.

Wieser, W.

Wong, B.

Yasuno, Y.

Yun, S.

Biomed. Opt. Express (3)

Opt. Express (5)

Opt. Lett. (2)

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Figures (8)

Fig. 1
Fig. 1 (a) The relationship between the absolute value of the scaling factor | §( m s ,z ) | , depth z, and shift m s . Here, m s is the relative k-shift between interferogram of interest A s and reference interferogram A r and m s 0 . N is the number of wavenumber samples in the interferogram. For a certain m s , | §( m s ,z ) | is depth dependent. At a certain depth, | §( m s ,z ) | is m s dependent. (b) The values for real and imaginary parts of the scaling factor §( m s ,z ) at a depth of z = 0.05N. At this depth, the value of m s can be obtained from the value of scaling factor.
Fig. 2
Fig. 2 Schematic of the posterior segment imaging swept-source OCT system.
Fig. 3
Fig. 3 An arbitrary interferogram from 200 background interferograms was taken as the reference interferogram A r (n) . The reference A r (n) was then subtracted from the remaining interferograms, and the differences were inverse Fourier transformed. The 200 A-lines were plotted and shown in (a), and the first 50 pixels in depth are shown in (b). The vertical green line in (b) shows the location of the residual fixed-pattern noise. Relative wavenumber (k) shifts were introduced between the reference interferogram and another of the 200 interferograms under evaluation In (c), the A-line under evaluation were reevaluated after subtracting the shifted interferograms by the reference interferogram. The green line with relative k-shift of 1 shows minimum value at the location of residual fixed-patter noise (c). The residual fixed-pattern noise amplitude was obtained by summing the A-line amplitude over 3 depth pixels centered at its peak (d). This was then evaluated as a function of the k-shift. The relative trigger jitter in k-space was found as the k-shift at which the fixed-pattern noise amplitude was minimized, + 1 in this case.
Fig. 4
Fig. 4 OCT intensity (top row) and Doppler (bottom row) images of a normal human retina. The images contained 3200 interferograms acquired by a circular scan pattern with diameter of 1.5 mm around the optic disk region in a healthy volunteer. Typical FD-OCT processing steps without interferogram alignment were used to obtain the figure (a). Firstly, the DC and lower frequency offset for each interferogram is removed by subtracting the mean of background interferograms. Then Gaussian-window spectral shaping, numerical dispersion compensation and inverse fast Fourier transform were applied. In (a), the green arrows indicate the residual fixed-pattern noise. To get figure (b), all the interferograms were re-aligned with the phase-based method A and FD-OCT processing steps were applied after that. In Figure (c), all the interferograms were re-aligned with the intensity-based method B and typical FD-OCT processing steps were applied after that. Figures (d), (e) and (f) are the corresponding Doppler OCT images for (a), (b) and (c). In Figs. (d), (e) and (f), the region indicated by the small black rectangle was utilized for the performance evaluation. The insets indicated by the large black rectangle are the magnified images of the smaller rectangle and used for the phase stability evaluation. The yellow arrows indicate the locations that have residual phase errors induced by trigger jitter. More reduced residual phase errors are found in (e) as compared to (d). No residual phase error is found in (f). The red arrows in (f) show blood vessels.
Fig. 5
Fig. 5 Doppler OCT retinal image from a diabetic patient. The volume scan covered a 1.6 × 2 mm2 area of the optic disc and had 80 B-scans with 600 A-lines per B-scan. One cross section corresponding to a vertical line scan was selected to compare results between methods. (a) Cross section image obtained using Bauman’s algorithm. Three regions were selected for signal-to-noise ratio (SNR) calculations. The SNR of Doppler phase shift (SNR_D) is the ratio of the average phase shift in a vessel and the standard deviation of the phase shift in static retinal tissue. The SNR of intensity (SNR_I) is the ratio of the average intensity in retina tissue and standard deviation of intensity in background. In this image, SNR_D = 6.65 and SNR_I = 27.86. (b) Cross section image obtained using wavenumber alignment method proposed here. In this image, SNR_D = 7.47 and SNR_I = 43.45.
Fig. 6
Fig. 6 Schematic of the OCT system with double delay lines in the reference arm. A Mach–Zehnder interferometer was used in the reference arm. One arm of the Mach–Zehnder interferometer was used to generate the fixed-pattern line in the image. The depth location of the fixed-pattern line can be tuned by changing the length of the corresponding delay line.
Fig. 7
Fig. 7 Minimization of fixed-pattern artifact and reduction of trigger jitter using method B for various situations. Columns a and b show the structure and Doppler OCT images of a sample (an infrared sensor card) without interferogram alignment. Columns c and d show the structure and Doppler OCT images of the sample after interferogram alignment using method B. The red arrows show the location of fixed-pattern lines. In row I, the fixed-pattern line is close to the maximum imaging range of the system. In row II, the fixed-pattern line is overlaid with sample image. In row III, the fixed -pattern line is a result of 1st order coherence revival. In row IV, the fixed-pattern line is a result of 2nd order coherence revival. In row V, there is no fixed-pattern noise and the residual amplitude for the sum of the first 20 pixels close to the zero delay was minimized with method B to reduce trigger jitter and improve the phase stability of the system.
Fig. 8
Fig. 8 Minimization of fixed-pattern artifact and reduction of trigger jitter using method B for a system with a constant sampling clock instead of an external optical k-clock. The OCT (a, b and e) and Doppler OCT (b, d and f) images of an infrared viewing card obtained before (a and b) and after (c,d,e and f) interferogram alignment are shown. Figures (c) and (d) are the OCT and Doppler OCT images after interferogram alignment on the original interferograms. Figures (e) and (f) are the OCT and Doppler OCT images after interferogram alignment on the 10 times upsampled interferograms. The images are obtained by direct Fourier transformation of the interferograms without resampling to a linear k-space. The reds arrows show location the fixed-pattern noise.

Equations (5)

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A s ( n )= A r ( n m s ),
F 1 [ A r ( n )]= I r ( z ),
F 1 [ A s ( n )]= I s ( z )= e i 2π N m s z I r ( z ),
I sr ( z )= I s ( z ) I r ( z )= I r ( z )§( m s ,z ),
m s =angle[ I s ( z f )]/ I r ( z f ) ]*N/(2π z f ),

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