## Resonant Doppler flow imaging and optical vivisection of retinal blood vessels

Optics Express, Vol. 15, Issue 2, pp. 408-422 (2007)

http://dx.doi.org/10.1364/OE.15.000408

Acrobat PDF (1998 KB)

### Abstract

For Fourier domain optical coherence tomography any sample movement during camera integration causes blurring of interference fringes and as such reduction of sensitivity for flow detection. The proposed method overcomes this problem by phase-matching a reference signal to the sample motion. The interference fringes corresponding to flow signal will appear frozen across the detector whereas those of static sample structures will be blurred resulting in enhanced contrast for blood vessels. An electro-optic phase modulator in the reference arm, driven with specific phase cycles locked to the detection frequency, allows not only for qualitative but also for quantitative flow detection already from the relative signal intensities. First applications to extract in-vivo retinal flow and to visualize 3D vascularization, i.e. optical vivisection, are presented.

© 2007 Optical Society of America

## 1. Introduction

1. R. Leitgeb, C. K. Hitzenberger, and A. F. Fercher, “Performance of Fourier domain vs. time domain optical coherence tomography,” Opt. Express **11**,889–894 (2003). [CrossRef] [PubMed]

4. G. Hausler and M. W. Lindner, “Coherence radar and spectral radar-new tools for dermatological diagnosis,” J. Biomed. Opt. **3**,21–31 (1998). [CrossRef]

7. R. Leitgeb, L. Schmetterer, W. Drexler, F. Berisha, C. Hitzenberger, M. Wojtkowski, T. Bajraszewski, and A. F. Fercher, “Real-time measurement of in-vitro and in-vivo blood flow with Fourier domain optical coherence tomography,” in *Coherence Domain Optical Methods And Optical Coherence Tomography In Biomedicine Viii*(2004), pp.141–146.

10. E. Gotzinger, M. Pircher, and C. K. Hitzenberger, “High speed spectral domain polarization sensitive optical coherence tomography of the human retina,” Opt. Express **13**,10217–10229 (2005). [CrossRef] [PubMed]

13. S. Makita, Y. Yasuno, T. Endo, M. Itoh, and T. Yatagai, “Polarization contrast imaging of biological tissues by polarization-sensitive Fourier-domain optical coherence tomography,” Appl. Opt. **45**,1142–1147 (2006). [CrossRef] [PubMed]

18. R. Leitgeb, M. Wojtkowski, A. Kowalczyk, C. K. Hitzenberger, M. Sticker, and A. F. Fercher, “Spectral measurement of absorption by spectroscopic frequency-domain optical coherence tomography,” Opt. Lett. **25**,820–822 (2000). [CrossRef]

26. J. W. You, T. C. Chen, M. Mujat, B. H. Park, and J. F. de Boer, “Pulsed illumination spectral-domain optical coherence tomography for human retinal imaging,” Opt. Express **14**,6739–6748 (2006). [CrossRef] [PubMed]

27. J. K. Barton and S. Stromski, “Flow measurement without phase information in optical coherence tomography images,” Opt. Express **13**,5234–5239 (2005). [CrossRef] [PubMed]

## 2. Theory

### 2.1. Chromatic interference fringe blurring

28. S. H. Yun, G. J. Tearney, J. F. de Boer, and B. E. Bouma, “Motion artifacts in optical coherence tomography with frequency-domain ranging,” Opt. Express **12**,2977–2998 (2004). [CrossRef] [PubMed]

*E*and the sample field

_{R}(k)*E*are expressed as functions of the wavenumber

_{S}(k)*k*. We further assume, in the most general case, a time dependent phase shift

*ϕ(t)*between the sample and the reference field. The recorded spectral interference signal, written as number of generated photo-electrons, becomes

*I*=

_{S,R}*E*

_{S,R}(k)E_{S,R}(k)^{*}, the asterisk denoting complex conjugate,

*z*

_{0}being the optical path length difference between sample and reference interface at

*t*=0,

*τ*the camera exposure time, and the proportionality factor

*γ*accounting for the detector conversion efficiency. Subsequently we will only consider the last part of Eq. (1) that actually contains information about the relative sample position. Denoting this part

*N*and assuming a phase shift

_{AC}(k)*ϕ(t)*that is linear in time, the integration yields [28

28. S. H. Yun, G. J. Tearney, J. F. de Boer, and B. E. Bouma, “Motion artifacts in optical coherence tomography with frequency-domain ranging,” Opt. Express **12**,2977–2998 (2004). [CrossRef] [PubMed]

*ϕ(τ)*is the total phase change during the integration time, and sinc(

*x*)≡sin(

*πx*)/(

*πx*). The varying phase

*ϕ*reduces the modulation depth of the spectral interference signal across the detector array. The origin of the phase shift can be manifold: often we are faced with involuntary sample movements, in particular during in-vivo measurements, or mechanical noise that causes statistical path length changes in the interferometer. In general, the phase change can be approximated as ΔΦ=

*β*+

*η(k-k*

_{0}

*)*with

*k*

_{0}being the central wavenumber. It comprises a constant phase term

*β*and a group dispersion term

*η*=d(ΔΦ)/d

*k*at

*k*

_{0}. For the case of a single interface in the sample arm, moving with a constant axial velocity

*V*, the phase shift can be written as ΔΦ=2

_{s}*kV*=2

_{S}τ*k*

_{0}Δ

*z*+2(

*k*-

*k*

_{0})Δ

*z*, i.e.

*β*=2

*k*

_{0}Δ

*z*and

*η*=2Δ

*z*. The change in optical path length Δ

*z*can also be introduced on purpose as in phase shifting FDOCT, using piezo actuators or electro-optic modulators (EOM). The latter case will involve higher order terms in

*k*for the resulting total phase shift due to the dispersion of the EOM crystal, which usually is Lithium Niobate (LiNbO

_{3}). An example for purely achromatic phase shifting, i.e.

*η*=0, has recently been given by employing acousto-optic frequency shifters to realize heterodyne FDOCT detection [29

29. A. H. Bachmann, R. A. Leitgeb, and T. Lasser, “Heterodyne Fourier domain optical coherence tomography for full range probing with high axial resolution,” Opt. Express **14**,1487–1496 (2006). [CrossRef] [PubMed]

*k*, we continue in calculating the FDOCT signal that is obtained by Fourier transforming Eq. (2) with respect to

*k*′=

*k*-

*k*

_{0}. Expressing the sinc-function in Eq. (2) as

*β*=0, i.e. a change in group dispersion, the original axial point spread function (PSF), which is determined by the temporal coherence function of the light source, is averaged and broadened, due to the convolution with a

*rect*function. However, for an exact signal analysis we need to take into account the complex exponential term exp(

*jβz*/

*η*) which is direct result from our spectral bandwidth centered at

*k*

_{0}.

*k*

_{FWHM}centered at

*k*

_{0}and writing the convolution in Eq. (3) explicitly one finds

*rect*-function is to change the integration borders to

*z*±

*η*/2. The result of this integral will exhibit two signal peaks, centered at

*z*=2

*z*

_{0}and

*z*=-2

*z*

_{0}, symmetric around the zero path delay due to the complex ambiguity of the FDOCT signal. Keeping only the peak at

*z*=2

*z*

_{0}, and using iterative partial integration together with the definition of the Hermite polynomial of order

*m*, H

*=(-1)*

_{m}*exp(*

^{m}*x*

^{2})

*d*(exp(-

^{m}*x*

^{2}))/

*dx*, gives

^{m}*αη*/

*β*. In case of a moving sample interface we have

*m*≥1 can be neglected. Upon using H

_{0}=1, the absolute value of the expression in Eq. (5) can then be simplified to

*z*

_{0}, i.e.(

*z*-2

*z*

_{0})=0 for a displacement during camera exposure Δ

*z*, yields

*sinc*-function. This is the result that would be expected for the achromatic case since it depends only on

*β*. The effect of the

*η*-term is an additional dampening factor that depends on the ratio between round trip coherence length 1/α and change in group dispersion

*η*. For the moving sample interface, the first zero of the

*sinc*-function is reached at Δ

*z*=

*λ*/2. Knowing the integration time

*τ*, the corresponding sample velocity is then expressed as

*V*=

_{s}*λ*/(2

*τ*). In the ideal achromatic case, the axial peak shape remains Gaussian. Plotting in Fig. 2 the axial peak shape for the moving sample interface as expressed by Eq. (6), it is revealed that the

*η*-term causes in addition peak broadening, which will eventually split up the signal and create two diverging signal peaks. The peak splitting is given by the width of the rect-function in Eq. (4) which in turn is equal to the displacement Δ

*z*. Nevertheless, as seen from Fig. (2), high SNR and large optical bandwidth is needed in order to observe this effect. Figure 3(a) indicates the normalized signal attenuation A(Δz), by plotting the normalized FDOCT signal peak heights [Eq. (6)] as a function of Δ

*z*.

### 2.2. Signal recovery by reference phase tuning

*-ΔΦ*

_{R}*. One immediately observes that for the phase matching condition*

_{S}*V*

_{π}(

*k*)=(2

*πa*-

*bk*)/(

*Qk*), the voltage at which for a certain wavenumber the phase is shifted by

*π*, together with the constants

*a*,

*b*and

*Q*, are provided by the manufacturer. The total change of the reference phase can be expressed as ΔΦ

*(*

_{R}*k*)=

*πΔV*/

*V*, with Δ

_{π}*V*being the change of voltage during integration time. A Taylor expansion of

*V*

_{π}(

*k*) yields

*β*=

*πQk*

_{0}Δ

*V*/(2

*πa*-

*bk*

_{0}) and

*η*=2

*π*

^{2}

*Qa*Δ

*V*/(2

*πa*-

*bk*

_{0})

^{2}. It is then possible to associate a reference path length shift Δ

*z*

_{R}to the

*β*-term as

*τ*, we can write for the corresponding reference speed

*V*=Δ

_{R}*z*/

_{R}*τ*, leading to a Doppler frequency of

*f*=

_{R}^{D}*k*

_{0}

*V*/

_{R}*π*. According to Eq. (8), this reference speed can compensate for the phase shift caused by sample movement, in particular of flow. For axial flow at constant speed

*V*we can write ΔΦ

_{S}*=2*

_{S}(k)*kV*. For

_{S}τ*V*=

_{S}*V*the

_{R}*β*-terms cancel out, but due to the group index of the EOM, the

*η*-terms will not compensate completely resulting in a signal peak broadening. Nevertheless, even for a large source bandwidth of 200

*nm*at a central wavelength of 800

*nm*, the difference to the ideally compensated situation will be smaller than 1

*dB*and can therefore be neglected. The important point is that the maximal detection sensitivity has been effectively shifted to the reference velocity

*V*, as shown in Fig. 3(b). It is worth noting that the maximum detectable velocity or Doppler frequency is independent of the Nyquist limit given by half the camera acquisition rate. The center Doppler frequency can in theory be shifted to arbitrary values only limited by the maximal EOM phase shift during camera exposure. It can be tuned to a particular velocity or associated Doppler frequency for which the sample Doppler frequency will be in resonance. The moving sample signal is then detected with high contrast whereas the signals of static structures are attenuated. The contrast between static and moving structures will be higher, the larger the actual sample velocity is.

_{R}### 2.3. Differential velocity mapping

*V*and an a priori unknown sample velocity

_{R}*V*. Since we know the reference velocity we also know the normalized signal attenuation A(

_{S}*V*) and A(

_{S}*V*-

_{S}*V*). Having measured a signal level of

_{R}*I*̂

^{0}for constant EOM voltage and a signal

*I*̂

^{φ}for the channel shifted by

*V*, we then can write

_{R}*SNR*=(

*I*̂

*/*

_{S}*δI*̂)

^{2}and assumed that the signal intensities are large as compared to the noise. The expression in Eq. (13) can be compared to the phase difference error of phase-sensitive Doppler FDOCT being [12

12. 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**,3931–3944 (2005). [CrossRef] [PubMed]

*δ(*Δ

*φ)*=1/√

*SNR*. The important difference is the dependence of the error on the signal attenuation for the static and the reference shifted channel A(

*V*) and A(

_{S}*V*-

_{S}*V*) respectively. The actual value of the absolute velocity error δ

_{R}*V*depends on δ

*Q*as well as on the local derivative of ΔA(

*V*) as shown in Fig. 4(b) as

_{S}*I*̂

^{φ},

*I*̂

^{-φ}and

*I*̂

^{0}(see Fig. 5(A)). The only restriction is that the three attenuation curves need a common intersection part of their main lobes. A differential analysis of the three tomograms allows to determine the axial velocity of any sample motion such as flow in the range [-λ

_{0}/(2τ), λ

_{0}/(2τ)] (see §4). Note that the velocity bandwidth is dependent on the camera exposure time

*τ*which is smaller than the camera line period T. The latter determines the unambiguous velocity bandwidth of phase-sensitive Doppler FDOCT as [-λ

_{0}/(4τ), λ

_{0}/(4τ)] [30

30. R. Leitgeb, L. Schmetterer, M. Wojtkowski, C. Hitzenberger, M. Sticker, and A. Fercher, “Flow Velocity Measurements by Frequency Domain Short Coherence Interferometry,” SPIE Proceedings **4619**,16–21 (2002). [CrossRef]

*V*is directly available. In principle a 3D reconstruction allows to extract the angle

_{ax}*θ*of a vessel with respect to the optical axis. The actual speed would then be obtained from

*V*=

*V*/cos(

_{ax}*θ*).

## 3. Experimental

*nm*and 853

*nm*and respective full-width-at-half-maximum values (FWHM) of 25

*nm*and 34

*nm*resulting in an overall FWHM of 36

*nm*, a central wavelength of 833.5

*nm*and an axial resolution of 8.5

*μm*in air. The light is first linearly polarized (Pol) in order to match the fast axis orientation of the EOM’s LiNbO

_{3}crystal. The reference arm contains the non-resonant EOM (NovaPhase) for phase shifting and a quarter waveplate in order to realize circular polarization. The EOM is driven by an arbitrary function generator (Agilent 33220A) followed by a high voltage amplifier (20x). The dispersion compensation matches both sample arm optics as well as the water chamber of the eye. The translation stage (TS) helps to adjust the reference to the sample arm length. The sample arm contains a LiNbO

_{3}crystal to match the dispersion of the EOM in the reference arm. The light is then expanded with a Galilei telescope of focal lengths f

_{1}=-40

*mm*and f

_{2}=100

*mm*. The light passes the X-Y galvo scanning stage (X-Y Sc) (Cambridge Technology) and illuminates the eye via lenses f

_{3}=60

*mm*and f

_{4}=30

*mm*. The optical power at the cornea is 300

*μW*which is safe for direct beam viewing according to the ANSI laser safety regulations [31]. After recombination, the reference and sample arm light is guided through a single mode fiber to the spectrometer module. The spectrometer is equipped with a volume diffraction grating (DG) (Wasatch, 1200lines/

*mm*), and an objective lens (OL) with focal length 135

*mm*. The CCD is a line scan camera (ATMEL AVIIVA, 2048 pixel, 12bit) where only 1024 elements are actually used. The camera is driven at a line rate of 17.4

*kHz*with an integration time of

*τ*=43

*μs*. The full covered spectral width is 68

*nm*resulting in a depth range in air of 2.6

*mm*. The beam waist at the cornea is 1.8

*mm*. The measured sensitivity is 98

*dB*close to the zero delay with a sensitivity decay of -7

*dB*/

*mm*.

*τ*=43

*μs*are ΔΦ

*=±2*

_{ref}(k)*π*at the center wavelength of 833.5

*nm*corresponding to a velocity of

*V*=

_{R}*λ*/2

*τ*=±9.7

*mm*/

*s*and an associated Doppler frequency of ±23.3

*kHz*. The transverse scanning is performed continuously with a theoretical spot size of 14

*μm*at the retina.

## 4. Results and discussion

32. P. Thevenaz, U. E. Ruttimann, and M. Unser, “A Pyramid Approach to Subpixel Registration Based on Intensity,” IEEE Transaction On Image Processing **7**,27–41 (1998). [CrossRef]

33. R. J. Zawadzki, S. M. Jones, S. S. Olivier, M. T. Zhao, B. A. Bower, J. A. Izatt, S. Choi, S. Laut, and J. S. Werner, “Adaptive-optics optical coherence tomography for high-resolution and high-speed 3D retinal in vivo imaging,” Opt. Express **13**,8532–8546 (2005). [CrossRef] [PubMed]

*V*/

*μs*in steps of 0.91

*V*/

*μs*during the recording of 81 tomograms. A single tomogram is acquired in 130

*ms*and consists of 2250 lateral points covering a range of 3

*mm*on the retina. Assuming the theoretic spot size of 14

*μm*we thus have 10.5

*x*over-sampling transversally. The recorded tomogram data has effectively three individual channels with 750 transverse points, each obtained quasi in parallel via the scheme outlined in Fig. 5(A): firstly, the standard FDOCT tomogram with attenuated flow signals due to interference fringe blurring [see Fig. 7(a)]; secondly, two tomograms where the static structure is gradually suppressed due to increasing EOM voltage slopes and the respective opposite flow signals are gradually enhanced [see Figs. 7(b) and 7(c)]. We chose a region in Figs. 7(b) and 7(c) where only static structure was present and calculated the average signal relative to the same region in the static channel [Fig. 7(a)] for each EOM voltage slope (triangles in Fig. 6). Each point represents an average over eight frames at the same voltage slope. As one can see, the measured structure attenuation deviates from the theoretical decay for higher voltage slopes. In order to explain this effect we calculated the MPA by referencing the average signal of the static structure within the indicated ROI in Fig. 7(a) to the average noise floor in the phase-shifted channels for each voltage slope (crosses in Fig. 6). The ROI was selected such that it contains only static structure avoiding flow signals. Along with the attenuation of the static structure the ratio of number of noise components to signal components within the ROIs of the phase-shifted channels increases. Thus, the signal attenuation will eventually reach the MPA value.

*log*(

*I*̂

^{φ}/

*I*̂

^{-φ}). In the logarithmic representation, the static structure is well suppressed whereas flow in opposite directions will have different signs and can easily be distinguished via appropriate adjustment of a grey level scale. This representation allows actually identifying roughly the velocity range by observing at which EOM voltage the flow signals will appear brightest or darkest. This in fact demonstrates clearly the idea of the resonant Doppler scheme. We observe that for vessels A and D [see Fig. 7(d)] the resonant region is situated at about ±6.4

*V*/

*μs*, corresponding to a flow velocity of approximately ±6.9

*mm*/

*s*, whereas for vessel B one finds a value at about -4.6

*V*/

*μs*with a corresponding velocity of -5

*mm*/

*s*. Only vessel C seems to gain gradually in contrast towards the maximum applied voltage slope of 8.2

*V*/

*μs*, hence

*V*>8.9

*mm*/

*s*. The high flow velocities present in vessel C exceed in fact the detection bandwidth. Only within the bandwidth the signal will be visible. This bandwidth is now shifted with reference velocity during the time sequence. In addition we have flow changes because of blood pulsation during the data acquisition. Those effects together manifest as rings within the vessel that seem to move radially during the sequence. The velocity values are estimates of ±0.9

*mm*/

*s*given the voltage slope step size of 0.91

*V*/

*μs*. Comparing tomograms Figs. 7(b) and 7(d) to Fig. 7(a), the strong contrast enhancement realized by the introduced method is particularly well visible for vessels A and C. Since we do not correct for bulk motion velocity artifacts [12

12. 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**,3931–3944 (2005). [CrossRef] [PubMed]

17. S. Makita, Y. Hong, M. Yamanari, T. Yatagai, and Y. Yasuno, “Optical coherence angiography,” Opt. Express **14**,7821–7840 (2006). [CrossRef] [PubMed]

*V*/

*μs*. The left column shows the logarithmically scaled differential images

*I*̂

^{φ}/

*I*̂

^{-φ},

*I*̂

^{φ}/

*I*̂

^{0}and

*I*̂

^{-φ}/

*I*̂

^{0}respectively with outlined vessels (A and B in Fig. 9). The right column shows the respective expected differential signal attenuation curves ΔA as function of flow velocity (cf. also Fig. 4). Combining the information of the three graphs, as is demonstrated for two selected vessels (A, B) in Fig. 9, one is able to find unique values for flow velocities via comparison and exclusion on a pure intensity basis. This can be easily realized by first observing from the upper row in Fig. 9 whether the corresponding velocity for a given intensity value is positive or negative. For a positive value one uses the red shaded range in the second row for unique velocity determination whereas for a negative value the blue shaded region in the third row. The maximum flow velocity which can be determined quantitatively is limited by the MPA value. We determined the MPA by calculating an average signal intensity and setting the MPA equal to the corresponding negative SNR, yielding MPA=-18.4

*dB*. This in turn gives a range of quantifiable velocity of ±8.76

*mm*/

*s*(green dashed line in Fig. 9) which is not achievable with phase-sensitive Doppler FDOCT due to fringe blurring.

*x*5-kernel was applied to the selected regions. The profile of vessel C has a flat top at 8.3

*mm*/

*s*since we hit the MPA limitation. The velocities in the central region of vessel C are too fast to be properly detected by at least two channels and quantitatively analyzed. The velocity calculation does not take into account any velocity offset due to proband motion. This explains the offset of the profile of vessel D with velocity peak value of -3.4

*mm*/

*s*and the sign change towards the edges of the vessel which is also visible for vessel A. The maximum velocity of vessel A is measured to be 5.2

*mm*/

*s*, whereas vessel D is at -5.1

*mm*/

*s*. According to Fig. 4(b), and assuming a typical SNR of 18.4

*dB*in our tomogram with dynamic range of 39

*dB*, the velocity error is ±550

*μm*/

*s*.

*V*/

*μs*in order to maximally contrast the vascular against the static structure for a 3D vessel sectioning. Each of the three sub-tomograms has 750 transverse points. A set of 81 tomograms was recorded vertically along a range of 4°. The 3D data set was recorded in 10.7

*s*. As for the previous measurement, motion artifacts are corrected by image registration.

## 5. Conclusion

## Acknowledgments

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24. | C. E. Riva, J. E. Grunwald, S. H. Sinclair, and B. L. Petrig, “Blood velocity and volumetric flow rate in human retinal vessels,” Invest. Ophthalmol. Visual Sci. |

25. | S. Yazdanfar, A. M. Rollins, and J. Izatt, “In vivo imaging of human retinal flow dynamics by color Doppleroptical coherence tomography,” Arch. Ophthalmol. |

26. | J. W. You, T. C. Chen, M. Mujat, B. H. Park, and J. F. de Boer, “Pulsed illumination spectral-domain optical coherence tomography for human retinal imaging,” Opt. Express |

27. | J. K. Barton and S. Stromski, “Flow measurement without phase information in optical coherence tomography images,” Opt. Express |

28. | S. H. Yun, G. J. Tearney, J. F. de Boer, and B. E. Bouma, “Motion artifacts in optical coherence tomography with frequency-domain ranging,” Opt. Express |

29. | A. H. Bachmann, R. A. Leitgeb, and T. Lasser, “Heterodyne Fourier domain optical coherence tomography for full range probing with high axial resolution,” Opt. Express |

30. | R. Leitgeb, L. Schmetterer, M. Wojtkowski, C. Hitzenberger, M. Sticker, and A. Fercher, “Flow Velocity Measurements by Frequency Domain Short Coherence Interferometry,” SPIE Proceedings |

31. | A. N. S. Institute, “American National Standards for Safe Use of Lasers, ANSI Z.136.1,” (2000). |

32. | P. Thevenaz, U. E. Ruttimann, and M. Unser, “A Pyramid Approach to Subpixel Registration Based on Intensity,” IEEE Transaction On Image Processing |

33. | R. J. Zawadzki, S. M. Jones, S. S. Olivier, M. T. Zhao, B. A. Bower, J. A. Izatt, S. Choi, S. Laut, and J. S. Werner, “Adaptive-optics optical coherence tomography for high-resolution and high-speed 3D retinal in vivo imaging,” Opt. Express |

**OCIS Codes**

(110.4500) Imaging systems : Optical coherence tomography

(110.6880) Imaging systems : Three-dimensional image acquisition

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

(170.4470) Medical optics and biotechnology : Ophthalmology

(170.4500) Medical optics and biotechnology : Optical coherence tomography

**ToC Category:**

Imaging Systems

**History**

Original Manuscript: October 27, 2006

Revised Manuscript: December 21, 2006

Manuscript Accepted: January 2, 2007

Published: January 22, 2007

**Virtual Issues**

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

**Citation**

Adrian H. Bachmann, Martin L. Villiger, Cedric Blatter, Theo Lasser, and Rainer A. Leitgeb, "Resonant Doppler flow imaging and optical vivisection of retinal blood vessels," Opt. Express **15**, 408-422 (2007)

http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-15-2-408

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