## Mobility and transverse flow visualization using phase variance contrast with spectral domain optical coherence tomography

Optics Express, Vol. 15, Issue 20, pp. 12636-12653 (2007)

http://dx.doi.org/10.1364/OE.15.012636

Acrobat PDF (815 KB)

### Abstract

Phase variance-based motion contrast is demonstrated using two phase analysis methods in a spectral domain optical coherence tomography system. Mobility contrast is demonstrated for an intensity matched Intralipid solution placed without flow within agarose wells. Vasculature oriented transversely to the imaging direction has been imaged for 3-4 dpf *in vivo* zebrafish using the phase variance contrast methods. 2D phase variance contrast images are demonstrated with imaging times only 25% higher than a Doppler flow image with comparable statistics. En face images created by integrating depth regions of 3D zebrafish intensity and phase variance contrast data demonstrate vasculature consistent with expected images.

© 2007 Optical Society of America

## 1. Introduction

7. A.F. Fercher, C.K. Hitzenberger, G. Kamp, and S.Y Elzaiat, “Measurement of intraocular distances by backscattering spectral interferometry,” Opt. Commun. **117**, 43 (1995). [CrossRef]

_{axial}(z), sometimes referred to as Doppler flow imaging, can be calculated using the average phase change at a given depth z for A-scans separated by time T:

*λ*designates the mean wavelength of the illumination light source and n is the refractive index of the material in which the phase measurement was taken. Previously demonstrated flow imaging techniques with SDOCT use successive A-scans to measure phase changes such that

*T*=

*τ*in Eq. (1) [8–10

8. A.F. Fercher, W. Drexler, C.K. Hitzenberger, and T. Lasser, “Optical coherence tomography - principles and applications,” Rep. Prog. Phys. **66**, 239 (2003). [CrossRef]

*v*

_{axial,max}(

*z*) = ±

*λ*/4

*nτ*.

11. B.H. Park, M.C Pierce, B. Cense, S.H. Yun, M. Mujat, G.J. Tearney, B.E. Bouma, and J.F. de Boer, “Realtime fiber-based multi-functional spectral-domain optical coherence tomography at 1.3 μm,” Opt. Express **13**, 3931 (2005). [CrossRef] [PubMed]

*in vivo*blood flow is also shown for vessel orientations perpendicular to the imaging direction.

## 2. Methods

### 2.1 Phase change limitations

_{scatterer}(z,T). The total phase change Δϕ(z,T) also contains the bulk motion of the entire sample along the imaging (axial) direction Δϕ

_{bulk}(T), caused by relative phase motion between the sample and the system and ideally is independent of depth z of the scatterers. Δϕ

_{SNR}(z) designates a phase error associated with the local SNR of the data calculated at the depth

*z*and is independent of time for a constant SNR. Experimental and theoretical results have determined that the standard deviation of SNR-limited phase error for phase changes has the form [11–13

11. B.H. Park, M.C Pierce, B. Cense, S.H. Yun, M. Mujat, G.J. Tearney, B.E. Bouma, and J.F. de Boer, “Realtime fiber-based multi-functional spectral-domain optical coherence tomography at 1.3 μm,” Opt. Express **13**, 3931 (2005). [CrossRef] [PubMed]

_{error,other}(z,T) encompasses the other phase errors which may occur for SDOCT phase measurements, including but not limited to phase changes caused by transverse motion across a scatterer at depth z [11

11. B.H. Park, M.C Pierce, B. Cense, S.H. Yun, M. Mujat, G.J. Tearney, B.E. Bouma, and J.F. de Boer, “Realtime fiber-based multi-functional spectral-domain optical coherence tomography at 1.3 μm,” Opt. Express **13**, 3931 (2005). [CrossRef] [PubMed]

_{bulk}(T), Δϕ

_{SNR}(z), and Δϕ

_{error,other}(z,T) have on the accuracy of phase measurements in a SDOCT system, improvements can be made to reduce the adverse effects of these terms in the phase contrast images.

### 2.2 Bulk phase removal

_{Δϕ,SNR}(z) has on the calculation of the bulk motion removal [9

9. B.R. White, M.C. Pierce, N. Nassif, B. Cense, B.H. Park, G.J. Tearney, B.E. Bouma, T.C. Chen, and J.F. de Boer., “In vivo dynamic human retinal blood flow imaging using ultra-high-speed spectral domain optical coherence tomography,” Opt. Express **11**, 3490 (2003). [CrossRef] [PubMed]

### 2.3 Phase variance contrast

_{bulk}(T) is determined by the summation of noise terms from Eq. (2):

^{2}

_{error,bulk}, which is the phase error created by the bulk motion subtraction method. The primary source of motion contrast information is σ

^{2}

_{Δϕ,scatterer}(z,T), With many types of motion, the measured variance of motion increases with the time separation between phase measurements T. At least three types of motion can be observed using the phase variance contrast of the scatterers, including but not limited to: (i) the axial component of motion caused by Brownian-type random motion, (ii) phase effects due to transverse motion of the sample [11

**13**, 3931 (2005). [CrossRef] [PubMed]

^{2}

_{Δϕ,scatterer}(z,T) compared to the other phase noise components.

### 2.4 MB-scan

*σ*

_{Δϕ}

^{2}(

*z*,

*T*

_{2})-

*σ*

_{Δϕ}

^{2}(

*z*,

*T*

_{1}), so the phase noise terms described in Eq. (5) which are independent in time such as the SNR limited phase error can be cancelled. The remaining contrast terms expected are σ

^{2}

_{Δϕ,scatterer}(z,T

_{2})- σ

^{2}

_{Δϕ,scatterer}(z,T

_{1}), which usually requires T

_{2}≫T

_{1}for significant motion changes. For the example of Brownian motion of diffusing spheres, the expected form of the variance of scatterer motion is σ

^{2}

_{Δϕ,scatterer}(z,T) = DT, where D is the diffusion constant. The calculated phase contrast

*σ*

_{Δϕ}

^{2}(

*z*,

*T*

_{2})-

*σ*

_{Δϕ}

^{2}(

*z*,

*T*

_{1}) in this case would be

*D*(

*T*

_{2}-

*T*

_{1})≈

*DT*

_{2}for T

_{2}≫T

_{1}.

^{2}

_{Δϕ}(z,T

_{2})-σ

^{2}

_{Δϕ}(z,T

_{1}) is plotted in Fig. 4(c) in the case of T

_{2}=1ms and T

_{1}=40μs, calculated from each time separation within the 200 A-scans acquired at each transverse location. The acquisition time of each M-scan collected is 8ms, resulting in a total data acquisition time of 1.6s for the image in this example. A threshold of

*σ*

_{Δϕ}

^{2}(

*z*,40

*μs*)≤1 is applied to the contrast image, corresponding to an intensity threshold level SNR

_{OCT}(

*z*)≥1 as described by Eq. (3) if the phase variance between successive A-scans is dominated by SNR-limited phase noise.

### 2.5 BM-scan

^{nd}image from bi-directional scanning or uni-directional scan with flyback).

^{2}

_{Δϕ}(z,T

_{2})- σ

^{2}

_{Δϕ}(z,T

_{1}) used for MB-scans is not ideal for use in a BM-scan because the phase variance measured for phase changes between successive A-scans σ

^{2}

_{Δϕ}(z,T

_{1}) where T

_{1}=τ contains additional phase errors (mentioned in Eq. (5) in the form of σ

^{2}

_{error,other}(z)) which do not occur in the measurement of σ

^{2}

_{Δϕ}(z,T

_{2}). These additional errors are created due to the transverse scanning occurring between the phase measurements of successive A-scans [11

**13**, 3931 (2005). [CrossRef] [PubMed]

^{2}

_{Δϕ}(z,T

_{1}) to remove the dominant SNR-limited noise term σ

^{2}

_{Δϕ,SNR}(z), numerical estimates of the phase error can be made to compensate for this effect based on theory.

^{2}= (ητ)

^{2}P

_{R}P

_{S}R(z)/(hν

_{0})

^{2}. The OCT noise N

^{2}is described by the shot noise distribution where the mean <N

^{2}> and the standard deviation σ

_{N2}of the noise are equal and <N

^{2}> =(ητ/hν

_{0})P

_{R}. The measured OCT signal Ĩ is a combination of the signal and noise components:

*I*is the same as used in Eq. (4) for bulk motion calculation, with the OCT intensity defined as 20log(

*I*) = 10log(|Ĩ|

^{2}). For this theory, it is assumed at the noise amplitude N remains approximately constant relative the phase of the noise term

*ϕ*, which is completely random. The magnitude of the OCT amplitude is calculated as:

_{N}^{2}〉 =

*S*

^{2}+ 〈N

^{2}〉. The OCT signal

*S*

^{2}is calculated by removing the OCT noise such that

*S*

^{2}= |〈|Ĩ|

^{2}〉-〈N

^{2}〉|. The absolute value function allows for log plotting of the signal data for noise terms below the expected mean noise level.

^{2}> for the OCT system was achieved by fitting the phase variance data against OCT signal for the regime where S≫N and is negligibly affected by the bulk motion compensation phase error. For the data presented in Fig. 5, phase data for the OCT intensity 10 - 25 dB above the noise level was fit to Eq. (3). Figure 5 plots this estimated phase error along and the measured phase error from 200 successive A-scans as a function of the normalized OCT signal. Instead of using a mirror with a reflectance reduced by a neutral density filter as the sample, the data acquired used a paper sample which is comprised of a range of reflections over the entire depth.

^{2}/<N

^{2}> ∼1, the discrepancy between the expected and measured phase error is most likely caused by the statistical variations of the noise, limiting the measurement of the interferometric signal. The measured phase error reaches a maximum level at approximately 3 radians

^{2}, which is caused by the imposed limitations of maximum phase changes between -π and +π. For a completely random distribution of phase changes between -π and +π, the standard deviation is approximately 1.8 radians. This limits the expected maximum phase variance measured for a purely noise situation to approximately 3.2 radians

^{2}. For the very high S

^{2}/<N

^{2}> case, the additional phase error introduced by the bulk motion removal algorithm has a non-negligible effect. Without using bulk motion removal, the measured phase error would be limited by the relative bulk motion between the system and sample.

## 3. Results and discussion

*in vivo*studies of vasculature imaging, 3-4 dpf (days post-fertilization) zebrafish (Danio rerio) were used. Zebrafish is ideal for imaging due to the fully developed vasculature system and the optical transparency of the animal. Figure 6 displays the anatomy and vasculature of a typical 3dpf zebrafish through confocal images and histological sections [15

15. “The Zebrafish Information Network”, www.zfin.org.

16. S. Isogai, M. Horiguchi, and B.M. Weinstein, “The vascular anatomy of the developing zebrafish: an atlas of embryonic and early larval development,” Developmental Biology **230**, 278 (2001). [CrossRef] [PubMed]

^{2}

_{Δϕ}(z,T

_{2})- σ

^{2}

_{Δϕ}(z,T

_{1}) with T

_{2}=1ms, T

_{1}=40μs calculated from 200 A-scans at each transverse location, and the imaging parameters chosen are the same as for the Intralipid imaging of Fig. 4(c). The locations identified with the arrows in this image correspond to the expected vessels identified in Fig. 6(b) and (c), labeled as the dorsal aorta and the axial vein. Figures 7(c) and (d) plot the Doppler images of the average phase change over successive A-scans for 10 and 100 total A-scans, respectively with the same intensity threshold as in Fig. 7(b). The only expected difference between these images is an increased suppression of the SNR-limited phase error due to increased averaging. The scale of these flow images is +/- 200μm/s, which corresponds to a phase change of +/- 0.12 radians for time separations of τ=40μs. The phase scale for these images has been chosen to be approximately 4% of the maximum possible dynamic range of phase changes because it is an efficient way to demonstrate the improved vascular visualization of very low axial flow velocities of the Doppler method through increased averaging of phase change data. One of the main limitations of the Doppler images is the SNR-limited phase noise. For a Doppler image dynamic range of +/- 0.12 radians created using a total of 10 A-scans, Eq. (3) is used to determine that the expected phase noise will be within this range for SNR

_{OCT}(

*z*)≤9dB. Further reductions to the phase noise occur with increased averaging to the calculated phase changes. Thresholds have been placed on the phase variance and Doppler images at the OCT intensity such that the signal is equal to the mean noise level in the system.

^{2}

_{Δϕ}(z,T

_{2})- σ

^{2}

_{Δϕ}(z,T

_{1}) imaged in Fig. 7(b) demonstrates phase change variance after the removal of SNR-limited phase noise. The value of this noise removal is demonstrated in Fig. 8, comparing phase variance σ

^{2}

_{Δϕ}(z,T

_{2}) with T

_{2}=1ms to the previously presented contrast image of Fig. 7(b). A threshold is applied to both images corresponding to an OCT intensity level such that SNR

_{OCT}(

*z*) ≥ 1. The effect of the noise removal in this case is clearly observed by this comparison.

_{2}=10ms. Due to the increased time between phase measurements used in this contrast implementation, the maximum axial flow velocity that can be quantitatively measured with a Doppler method without phase wrapping is 250 times smaller than for successive A-scan phase changes in this system. To reduce the total imaging time required for the phase contrast image, 5 total B-scans were used to create the BM-scan data resulting in a total image acquisition time of 50ms. With the resulting reduced statistics for the phase contrast image, median filters were applied (3 pixels transverse, 3 pixels axially) to reduce the noise observed in the image.

^{2}

_{Δϕ}(z,T) after the removal of the estimated phase noise described by Eq. (3), with a threshold applied based on the OCT intensity signal such that SNR

_{OCT}(

*z*)≤1. The arrows in Fig. 9(a) and (b) highlight areas corresponding to the dorsal aorta and axial vein regions identified using the MB-scan data in Fig. 7. These expected locations correspond to the contrast visualization occurring in the BM-scan phase contrast image. Additional phase variance contrast was also observed below the expected regions for the blood vessels. With the increased time between phase measurements as compared to the MB-scan, shadowing artifacts are now present below the regions of transverse blood flow due to the refractive index variations created within the vessels.

_{0}, calculation of phase change variance requires at least four independent phase changes for adequate statistics, allowing for a maximum time separation of T

_{0}/4 for phase changes. The demonstrated MB-scan technique created a 200 transverse pixel contrast image using M-scans composed of 200 A-scans for a total acquisition time of 1.6s, which results in a maximum time between phase changes of 2ms for proper statistics of phase variance. Reducing the time duration of each M-scan of the MB-scan would lower the total imaging time of the contrast image, but would also shorten the maximum time between phase changes that can be determined and reduce the motion contrast observed.

## 4. Conclusion

## Appendix

## Deriving SNR and phase noise for shot noise limited OCT performance

_{R}and power from the sample arm arriving at the spectrometer is P

_{S}. Assume that P

_{S}≪ P

_{R}. Integration time of spectrometer is τ and the spectrometer contains M pixels used in k-space measurements. In terms of the number of electrons converted by the CCD of the spectrometer, the measurement in k-space is of the form:

*S*(

_{j}*k*) is the interferometric signal is defined as

_{j}at optical path difference z

_{j}=2(z

_{Sj}- z

_{R}) of interferometer. The summation of this signal is taken over all of the sample reflections. Define

*F*(

_{DC}*k*) +

*N*(

*k*) combine to form the shot noise distribution of electrons. The mean number of electrons is given by

*F*(

_{DC}*k*) =

*ηP*(

_{R}*k*)

*τ*/

*hv*, where

*η*is the combined light collection and electron conversion efficiency of the spectrometer for photons of energy

*hv*.

*N*(

*k*) is the random portion of the Gaussian distribution with variance

*σ*

^{2}

_{N(k)}=

*ηP*(

_{R}*k*)

*τ*/

*hv*and zero mean. Using the property of Fourier transforms

*FT*(

*A*+

*B*) =

*FT*(

*A*) +

*FT*(

*B*), the Fourier transform of F(k) produces the OCT intensity amplitude

*Ĩ*(

*z*):

_{j}≥ 0 for all reflection locations be taken into account as well. These assumptions lead to:

## Interferometric Signal

*kz*+

_{j}*ϕ*) = cos(

_{Si}*kz*)cos(

_{j}*ϕ*)-sin(

_{Sj}*kz*)sin(

_{j}*ϕS*):

_{j}*S*(

_{j}*k*) changes slowly compared to cos(

*kz*) and sin(

_{j}*kz*). With this assumption make the approximation for the summation:

_{j}## Shot Noise Analysis

*f*(

*k*))* =

*f*(

*k*).

*N*(

*k*)〉 = 0 :

_{Re}(z), N

_{Im}(z) of the Fourier transform of the noise distribution N(k) are random Gaussian distributions, all centered around zero mean such that 〈

*N*(

*k*)〉 = 〈

*N*

_{Re}(

*z*)〉 = 〈

*N*

_{Im}(

*z*)〉 = 0. With each component being independent of each other, the phase of the noise

*ϕ*(

_{N}*z*) is completely random. Determining the properties of the noise components:

_{Re}(z), N

_{Im}(z) have identical distributions, which means that σ

_{NRe}

^{2}=σ

_{NIm}

^{2}. Therefore:

^{2}is calculated:

## OCT Calculations

*ϕ*is completely random:

_{N}## SNR Definition

^{2}where the reflection R=1 to the standard deviation of the noise magnitude:

## Definition of Phase Noise

*z*), the calculated phase

*ϕ*(

*z*) can deviate from the expected sample phase

*ϕ*(

_{S}*z*) depending on the relative noise properties. To determine the noise effects on the error on phase measurements, a probability analysis of the phase is required. Since the phase accuracy does not depend on the sample phase, set

*ϕ*(

_{S}*z*) = 0 for convenience. Using Eq. (27) in this case, the phase can be determined through trigonometry. The noise components N

_{Re}(z) and N

_{Im}(z) have the same Gaussian distribution described earlier in Eq. (23). For the case where S ≫ N, the phase determination can be simplified.

*ϕ*(

*z*) in this case is calculated from the probability distribution of the noise using each OCT signal component S(z)

^{2}:

^{2}(z) requires two phase measurements, each with phase error associated with it. The phase variance determined for phase changes is twice the value of the error for a single phase measurement.

## Acknowledgments

## References and links

1. | S.O. Sykes, N.M. Bressler, M.G. Maguire, A.P. Schachat, and S.B. Bressler, “Detecting recurrent choroidal neovascularization. Comparison of clinical examination with and without fluorescein angiography,” Arch. Ophthalmology |

2. | J.D. Gass, “Stereoscopic atlas of macular diseases,” 4th ed. (Mosby, 1997). |

3. | L.A. Yannuzzi, K.T. Rohrer, L.J. Tindel, R.S. Sobel, M.A. Costanza, W. Shields, and E. Zang, “Fluorescein angiography complication survey,” Ophthalmology |

4. | M. Hope-Ross, L.A. Yannuzzi, E.S. Gragoudas, D.R. Guyer, J.S. Slakter, J.A. Sorenson, S. Krupsky, D.A. Orlock, and C.A. Puliafito, “Adverse reactions to indocyanine green,” Ophthalmology |

5. | 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,” Science |

6. | W. Drexler, U. Morgner, F.X. Kartner, C. Pitris, S.A. Boppart, X.D. Li, E.P. Ippen, and J.G Fujimoto, “In vivo ultrahigh resolution optical coherence tomography,” Opt. Lett. |

7. | A.F. Fercher, C.K. Hitzenberger, G. Kamp, and S.Y Elzaiat, “Measurement of intraocular distances by backscattering spectral interferometry,” Opt. Commun. |

8. | A.F. Fercher, W. Drexler, C.K. Hitzenberger, and T. Lasser, “Optical coherence tomography - principles and applications,” Rep. Prog. Phys. |

9. | B.R. White, M.C. Pierce, N. Nassif, B. Cense, B.H. Park, G.J. Tearney, B.E. Bouma, T.C. Chen, and J.F. de Boer., “In vivo dynamic human retinal blood flow imaging using ultra-high-speed spectral domain optical coherence tomography,” Opt. Express |

10. | R.A. Leitgeb, L. Schmetterer, C.K. Hitzenberger, A.F. Fercher, F. Berisha, M. Wojtkowski, and T. Bajraszewski, “Real-time measurement of in vitro flow by Fourier-domain color Doppler optical coherence tomography,” Opt. Lett. |

11. | B.H. Park, M.C Pierce, B. Cense, S.H. Yun, M. Mujat, G.J. Tearney, B.E. Bouma, and J.F. de Boer, “Realtime fiber-based multi-functional spectral-domain optical coherence tomography at 1.3 μm,” Opt. Express |

12. | S. Yazdanfar, C.H. Yang, M.V. Sarunic, and J.A. Izatt, “Frequency estimation precision in Doppler optical coherence tomography using the Cramer-Rao lower bound,” Opt. Express |

13. | B. Vakoc, S.H. Yun, J.F. de Boer, G.J. Tearney, and B.E. Bouma, “Phase-resolved optical frequency domain imaging,” Opt. Express |

14. | S. Makita, Y. Hong, M. Yamanari, T. Yatagai, and Y. Yasuno, “Optical Coherence Angiography,” Opt. Express |

15. | “The Zebrafish Information Network”, www.zfin.org. |

16. | S. Isogai, M. Horiguchi, and B.M. Weinstein, “The vascular anatomy of the developing zebrafish: an atlas of embryonic and early larval development,” Developmental Biology |

**OCIS Codes**

(110.4500) Imaging systems : Optical coherence tomography

(120.5050) Instrumentation, measurement, and metrology : Phase measurement

(170.3880) Medical optics and biotechnology : Medical and biological imaging

(170.4500) Medical optics and biotechnology : Optical coherence tomography

**ToC Category:**

Imaging Systems

**History**

Original Manuscript: May 11, 2007

Revised Manuscript: September 11, 2007

Manuscript Accepted: September 13, 2007

Published: September 18, 2007

**Virtual Issues**

Vol. 2, Iss. 11 *Virtual Journal for Biomedical Optics*

**Citation**

Jeff Fingler, Dan Schwartz, Changhuei Yang, and Scott E. Fraser, "Mobility and transverse flow visualization using phase variance contrast with spectral domain optical coherence tomography," Opt. Express **15**, 12636-12653 (2007)

http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-15-20-12636

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### References

- S. O. Sykes, N. M. Bressler, M. G. Maguire, A. P. Schachat and S. B. Bressler, "Detecting recurrent choroidal neovascularization. Comparison of clinical examination with and without fluorescein angiography," Arch. Ophthalmology 112, 1561 (1994). [CrossRef]
- J. D. Gass, "Stereoscopic atlas of macular diseases," 4th ed., (Mosby, 1997).
- L. A. Yannuzzi, K. T. Rohrer, L. J. Tindel, R. S. Sobel, M. A. Costanza, W. Shields and E. Zang, "Fluorescein angiography complication survey," Ophthalmology 93, 611 (1986). [PubMed]
- M. Hope-Ross, L. A. Yannuzzi, E. S. Gragoudas, D. R. Guyer, J. S. Slakter, J. A. Sorenson, S. Krupsky, D. A. Orlock and C. A. Puliafito, "Adverse reactions to indocyanine green," Ophthalmology 101, 529 (1994). [PubMed]
- 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," Science 254, 1178 (1991). [CrossRef] [PubMed]
- W. Drexler, U. Morgner, F. X. Kartner, C. Pitris, S. A Boppart, X. D. Li, E. P. Ippen and J. G. Fujimoto, "In vivo ultrahigh resolution optical coherence tomography," Opt. Lett. 24, 1221 (1999). [CrossRef]
- A. F. Fercher, C. K. Hitzenberger, G. Kamp and S. Y. Elzaiat, "Measurement of intraocular distances by backscattering spectral interferometry," Opt. Commun. 117, 43 (1995). [CrossRef]
- A. F. Fercher, W. Drexler, C. K. Hitzenberger and T. Lasser, "Optical coherence tomography - principles and applications," Rep. Prog. Phys. 66, 239 (2003). [CrossRef]
- B. R. White, M. C. Pierce, N. Nassif, B. Cense, B. H. Park, G. J. Tearney, B. E. Bouma, T. C. Chen and J. F. de Boer., "In vivo dynamic human retinal blood flow imaging using ultra-high-speed spectral domain optical coherence tomography," Opt. Express 11, 3490 (2003). [CrossRef] [PubMed]
- R. A. Leitgeb, L. Schmetterer, C. K. Hitzenberger, A. F. Fercher, F. Berisha, M. Wojtkowski and T. Bajraszewski, "Real-time measurement of in vitro flow by Fourier-domain color Doppler optical coherence tomography," Opt. Lett. 29, 171 (2004). [CrossRef] [PubMed]
- B.H. Park, M.C Pierce, B. Cense, S.H. Yun, M. Mujat, G.J. Tearney, B.E. Bouma and J.F. de Boer, "Real-time fiber-based multi-functional spectral-domain optical coherence tomography at 1.3 µm," Opt. Express 13, 3931 (2005). [CrossRef] [PubMed]
- S. Yazdanfar, C. H. Yang, M. V. Sarunic and J. A. Izatt, "Frequency estimation precision in Doppler optical coherence tomography using the Cramer-Rao lower bound," Opt. Express 13, 410 (2005). [CrossRef] [PubMed]
- B. Vakoc, S. H. Yun, J. F. de Boer, G. J. Tearney and B. E. Bouma, "Phase-resolved optical frequency domain imaging," Opt. Express 13, 5483 (2005). [CrossRef] [PubMed]
- S. Makita, Y. Hong, M. Yamanari, T. Yatagai and Y. Yasuno, "Optical Coherence Angiography," Opt. Express 14, 7821 (2006). [CrossRef] [PubMed]
- "The Zebrafish Information Network," www.zfin.org.
- S. Isogai, M. Horiguchi and B. M. Weinstein, "The vascular anatomy of the developing zebrafish: an atlas of embryonic and early larval development," Developmental Biology 230, 278 (2001). [CrossRef] [PubMed]

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