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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editor: Gregory W. Faris
  • Vol. 5, Iss. 8 — Jun. 8, 2010
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Ultrahigh sensitive optical microangiography for in vivo imaging of microcirculations within human skin tissue beds

Lin An, Jia Qin, and Ruikang K Wang  »View Author Affiliations


Optics Express, Vol. 18, Issue 8, pp. 8220-8228 (2010)
http://dx.doi.org/10.1364/OE.18.008220


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Abstract

In this paper, we demonstrate for the first time that the detailed cutaneous blood flow at capillary level within dermis of human skin can be imaged by optical micro-angiography (OMAG) technique. A novel scanning protocol, i.e. fast B scan mode is used to achieve the capillary flow imaging. We employ a 1310nm system to scan the skin tissue at an imaging rate of 300 frames per second, which requires only ~5 sec to complete one 3D imaging of capillary blood flow within skin. The technique is sensitive enough to image the very slow blood flows at ~4 μm/sec. The promising results show a great potential of OMAG’s role in the diagnosis, treatment and management of human skin diseases.

© 2010 OSA

1. Introduction

2. Methods

To achieve ultrahigh sensitive imaging to the flow, we applied a novel scanning protocol in this system. Firstly, for each B scan (i.e. x-direction scan), we acquired 128 A-lines with a spacing of ~15 μm between adjacent lines, thus covering a size of ~2 mm on the tissue. The imaging rate was 300 frames per second (fps). Note that with 47 kHz line scan rate, the theoretical imaging rate should be 367 fps. The reduced imaging rate at 300 fps was due to the data transfer limitations during the handshake between the camera and the computer. Secondly, in y-direction (i.e. C scan direction), we captured 1500 B-scans over 2.0 mm on the tissue, which gave a ~1.3 μm spacing between adjacent B scans, indicating the oversampling factor of ~12 in the C scan direction. The whole 3D data volume was captured within 5 s.

The essential principle of UHS-OMAG is the same as the traditional one [20

20. R. K. Wang and L. An, “Doppler optical micro-angiography for volumetric imaging of vascular perfusion in vivo,” Opt. Express 17(11), 8926–8940 (2009). [CrossRef] [PubMed]

], except that the OMAG algorithm is applied on slow axis (C scan direction) rather than fast axis (B scan direction). As analyzed in [20

20. R. K. Wang and L. An, “Doppler optical micro-angiography for volumetric imaging of vascular perfusion in vivo,” Opt. Express 17(11), 8926–8940 (2009). [CrossRef] [PubMed]

], the interference signal of one B-scan captured by the CCD camera can be expressed as the following equation:
I(t,k)=2S(k)ER[a(z,t)cos(2kn(t)z)dz+a(z1)cos[2kn(t)(z1vt)]]
(1)
where k is the wavenumber; t is the timing when a A-line was captured. ER is the light reflected from the reference mirror; S(k) is the spectral density of the light source used; n is the refractive index of tissue; z is the depth coordinate; a(z, t) is the amplitude of the back scattered light; v is the velocity of moving blood cells in a blood vessel, which is located at depth z1. Because the light backscattered from the sample is quite weak compared to the light reflected from the reference mirror, we do not consider, in Eq. (1), the self cross-correlation between the light backscattered from different positions within the sample. We also do not consider the DC signals because they do not contribute to useful OMAG signals. The conventional OMAG used high pass filtering in the fast scanning axis, i.e. B scan direction, to isolate the optical scattering signals between the static and moving scatters. Thus, the detectable flow velocity is determined by the time spacing, ΔtB, between the adjacent A scans, i.e., v=λ/2nΔtB. If flow velocity in a capillary is v ≤ 100 μm/s, then it would require ΔtB ≥ ~4.7 ms for the system to have a chance to sample the blood cells flowing in the capillary. This time spacing translates into a scanning speed of ~213 A scans per second. Therefore, the total imaging time to acquire a 3D capillary flow image of a tissue volume would be prohibitively long, not ideal for in vivo imaging of capillary blood flows.

In order to image the slow blood flow within capillary vessels while keeping the imaging time at the same order as the conventional approach, we propose to perform the OMAG algorithm along the C scan direction. In this case, Eq. (1) can still be used to represent the spectral interferogram signal captured by the system, except that the time variable, t, is now corresponding to the B-scan numbers in one C-scan. With this modification, the requirement of the oversampling in the B scan direction as in the conventional OMAG system is relaxed, making it possible to have a much faster B scan imaging rate, provided that the line scan camera in the spectrometer is limited or fixed. The detectable flow velocity is determined by the time spacing, ΔtC, between adjacent B scans. In our system setup, the imaging rate is 300 fps, i.e., ΔtC ~3.3 ms. Therefore, considering that the C scan direction is densely sampled at an oversampling factor of 12, the detectable flow velocity would be ~141 μm/s while the imaging speed is still kept at 47,000 A scans per second. This detectable flow velocity would be sufficient to image the blood flow in capillaries.

In the data processing, the proposed approach first takes a differential operation on the captured B scan spectral interferograms along the C scan direction, i.e.,
Iflow(ti,k)=I(ti,k)I(ti1,k),i=1,2,3...1500
(2)
where i represents the index of the B scans in the C scan direction. The differential operation is equivalent to the high pass filtering, which suppresses the optical scattering signals from the static elements within scanned tissue volume. Then, we apply fast Fourier transform (FFT) upon every wavenumber k (t is now constant) of Eq. (2) to obtain the depth resolved OMAG flow image with ultrahigh sensitivity to the flow.

The minimum detectable blood flow is determined by the system phase noise floor, which can be expressed by the intensity signal to noise ratio, S, of the OMAG/OCT system by σΔφ2=1/S [22

22. B. J. Vakoc, S. H. Yun, J. F. de Boer, G. J. Tearney, and B. E. Bouma, “Phase-resolved optical frequency domain imaging,” Opt. Express 13(14), 5483–5493 (2005). [CrossRef] [PubMed]

]. Thus, with the system signal to noise ratio at 85 dB, the minimum detectable flow velocity would be ~4.0 μm/s. However, bear in mind that if a blood cell moves at 4μm/s, the current OMAG system would not provide a continuous trajectory for this blood cell in the 3D OMAG flow image, i.e., the trajectory would be seen as a broken line.

3. Experimental results

Because the conventional OMAG requires oversampling at the fast scanning direction (i.e., B scan), it is not sensitive to the slow blood flow within the capillaries, which are normally below 100μm/s. However, the conventional PRODT approach totally failed in imaging any of blood vessels [see Fig. 1(F)]. It should be noted that there is seen global noise ‘flow’ background in the UHS-OMAG flow image, e.g., in Fig. 2(B)
Fig. 2 , Cross sectional imaging of a flow phantom in which the intralipid scattering fluid in the capillary is not flowing. (A) B-scan structural image, and corresponding (B) ultrahigh sensitive OMAG flow image, indicating the Brownian motion of particles. White bar = 500 μm.
, which might be caused by some ‘non-moving’ scatters, such as global motion etc. In this case, the moving-scatter-sensitive optical Doppler OCT technique proposed in [23

23. H. W. Ren, T. Sun, D. J. MacDonald, M. J. Cobb, and X. D. Li, “Real-time in vivo blood-flow imaging by moving-scatterer-sensitive spectral-domain optical Doppler tomography,” Opt. Lett. 31(7), 927–929 (2006). [CrossRef] [PubMed]

,24

24. H. Ren and X. Li, “Clutter rejection filters for optical Doppler tomography,” Opt. Express 14(13), 6103–6112 (2006). [CrossRef] [PubMed]

] may be used to further enhance the UHS-OMAG flow imaging quality.

In order to check whether the flow sensitivity of UHS-OMAG approaches the system phase-noise floor (in this case ~4 μm/s as stated in the last section), we used instead a highly scattering flow phantom as the imaging target. The phantom was made of the gelatin mixed with ~1% milk to simulate the background optical heterogeneity of the tissue. In making this background tissue, precaution was taken so that the mixed gel was well solidified to minimize the possible Brownian motion of particles in the background. A capillary tube with an inner diameter of ~400 μm was submerged in this background tissue and ~2% TiO2 particle solution was flowing in it that was controlled by a precision syringe pump. Although such setup can control precisely the flow velocity in the capillary tube, the flow speed as low as ~4 μm/s is difficult, if not impossible, to provide. Considering if the flow is stopped, the Brownian motion of particles is unavoidable in the capillary tube. With our experimental condition, the motion speed of particles due to Brownian motion would be randomly distributed within a range of several tens of microns per second. Due to these reasons, we decided to test whether UHS-OMAG is able to measure the Brownian motion of particles. In the experiments, the capillary tube was made almost perpendicular to the incident sample beam to avoid free fall of the scattering particles within the tube. The imaging results are shown in Fig. 2, where Fig. 2(A) is the OMAG/OCT microstructural image of the flow phantom, and Fig. 2(B) is the corresponding UHS-OMAG flow image. From this result, it is clear that UHS-OMAG is able to image the particle movements due to Brownian motion while almost no signals are detected in the background region.

To examine in more detail, we used the phase-resolved technique [6

6. Y. H. Zhao, Z. P. Chen, Z. H. Ding, H. Ren, and J. S. Nelson, “Real-time phase-resolved functional optical coherence tomography by use of optical Hilbert transformation,” Opt. Lett. 27(2), 98–100 (2002). [CrossRef]

, 20

20. R. K. Wang and L. An, “Doppler optical micro-angiography for volumetric imaging of vascular perfusion in vivo,” Opt. Express 17(11), 8926–8940 (2009). [CrossRef] [PubMed]

] applied to the adjacent B-scans of the UHS-OMAG flow images to provide the velocity image of the flow phantom above. The result is shown in Fig. 3(A)
Fig. 3 , Assessment of UHS-OMAG sensitivity to the flow as compared to PRODT. (A) velocity image obtained from the flow phantom assessed by UHS-OMAG, (B) plot of the velocity data across the capillary tube at the position shown as the blue line in (A). (C) and (D) are the corresponding results obtained by PRODT imaging of the same phantom, respectively. White bar = 500 μm.
, where it can be seen that the velocity values in the background region are low while those within the capillary tube are contrasted out primarily due to the Brownian motion of the particles. Figure 3(B) shows a plot of the calculated velocities across the center of the capillary tube at the position marked as the blue line in Fig. 3(A), where the dashed box indicates the position of the capillary lumen. The velocity values of particle movements ranged from approximately −50 to 100 μm/s at this cross-line position. The standard deviation of the values outside the dashed-box region was evaluated to be ~4.5 μm/s, close to the theoretical value of ~4 μm/s. From this experiment, we concluded that the proposed UHS-OMAG is sensitive to the flow as low as ~4 μm/s for the system setup used in this study. We also performed the conventional PRODT imaging of the same phantom. In doing so, we set the system imaging rate at 31,000 A scans per second. And the A-line density across the B-scan of ~2.5 mm was set at 4000, indicating the spacing between adjacent A scans was 0.625 μm. The corresponding results are given in Fig. 3(C) and 3(D), respectively, where it is clear that PRODT was totally failed to image the Brownian motion of the particles under the current experimental setup. Note also that the standard deviation of velocity values shown in Fig. 3(D) was ~180 μm/s, thus it is not surprising that PRODT is not able to achieve satisfactory imaging performance.

The 3D OMAG imaging result of blood vessel networks is given in Fig. 4(C), shown together with the 3D micro-structural image. To see the OMAG flow signals in more detail, we provide a movie in Fig. 4(D) to show the enface view flying through from the top to the bottom, where the blood flows within blood vessel systems within the skin are clearly delineated. Because the UHS-OMAG sensitivity is as low as ~4μm/s, even the dynamics of sweat glands are imaged. In Fig. 5
Fig. 5 UHS-OMAG provides detailed projection views of microcirculation network at different depths of skin obtained from: (A) 400 – 450μm (closely representing papillary dermis), (B) 450 – 650μm, (C) 650-780μm (closely representing reticular dermis) and (D) 780 – 1100μm (part of hypodermis), respectively. The strength of reflectance signals in the images is displayed within a range between 20dB (dark) and 50 dB (bright).
, we provide the projection views at the different land-mark depths. Figure 5(A) gives the projection view at the depths from 400 to 450μm, which depth corresponds to the papillary dermis where the capillary vessels are dense (e.g., pointed by the arrows). At the depths from 450 to 650μm, the vessels are almost vertical that connects vessel networks between papillary dermis and reticular dermis, seen as the bright spots in Fig. 5(B). The blood vessel network in reticular dermis is given in Fig. 5(C) where the vessel diameter is seen to be smaller than those situated in the hypodermis in Fig. 5(D). These observations from ultrahigh sensitive OMAG are almost identical to that described in the standard reference [25

25. I. M. Braverman, “The Cutaneous Microcirculation,” J. Investig. Dermatol. Symp. Proc. 5(1), 3–9 (2000). [CrossRef]

], for example given in Fig. 4(A), demonstrating the power of the ultrahigh sensitive OMAG in the investigations of pathological conditions in dermatology.

4. Conclusion

We have demonstrated an ultrahigh sensitive OMAG system to image the volumetric microcirculation within the human skin. It was achieved by applying the OMAG algorithm along the slow scan axis (i.e., the C scan direction), as opposed to the fast axis (i.e., the B scan direction) in the conventional method. Comparing with the conventional OMAG flow image, the new method delivered much better performance to extract slow flow information. We have shown that detailed 3D microvascular images obtained from the human skin by the proposed OMAG is comparable to that described in the standard textbook. Therefore, we expect that the ultrahigh sensitive OMAG may have great value in future clinical investigations of pathological conditions in human skin.

Acknowledgement

This work was supported in part by research grants from the National Heart, Lung, and Blood Institute (R01 HL093140), National Institute of Biomedical Imaging and Bioengineering (R01 EB009682), and the American Heart Association (0855733G). The content is solely the responsibility of the authors and does not necessarily represent the official views of grant giving bodies.

References and links

1.

M. Stücker, V. Baier, T. Reuther, K. Hoffmann, K. Kellam, and P. Altmeyer, “Capillary blood cell velocity in human skin capillaries located perpendicularly to the skin surface: measured by a new laser Doppler anemometer,” Microvasc. Res. 52(2), 188–192 (1996). [CrossRef] [PubMed]

2.

J. D. Briers, “Laser Doppler, speckle and related techniques for blood perfusion mapping and imaging,” Physiol. Meas. 22(4), 201 (2001). [CrossRef]

3.

H. F. Zhang, K. Maslov, G. Stoica, and L. V. Wang, “Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging,” Nat. Biotechnol. 24(7), 848–851 (2006). [CrossRef] [PubMed]

4.

A. F. Fercher, W. Drexler, C. K. Hitzenberger, and T. Lasser, “Optical coherence tomography – principles and applications,” Rep. Prog. Phys. 66(2), 239–303 (2003). [CrossRef]

5.

P. H. Tomlins and R. K. Wang, “Theory, development and applications of optical coherence tomography,” J. Phys. D Appl. Phys. 38(15), 2519–2535 (2005). [CrossRef]

6.

Y. H. Zhao, Z. P. Chen, Z. H. Ding, H. Ren, and J. S. Nelson, “Real-time phase-resolved functional optical coherence tomography by use of optical Hilbert transformation,” Opt. Lett. 27(2), 98–100 (2002). [CrossRef]

7.

B. J. Vakoc, R. M. Lanning, J. A. Tyrrell, T. P. Padera, L. A. Bartlett, T. Stylianopoulos, L. L. Munn, G. J. Tearney, D. Fukumura, R. K. Jain, and B. E. Bouma, “Three-dimensional microscopy of the tumor microenvironment in vivo using optical frequency domain imaging,” Nat. Med. 15(10), 1219–1223 (2009). [CrossRef] [PubMed]

8.

A. H. Bachmann, M. L. Villiger, C. Blatter, T. Lasser, and R. A. Leitgeb, “Resonant Doppler flow imaging and optical vivisection of retinal blood vessels,” Opt. Express 15(2), 408–422 (2007). [CrossRef] [PubMed]

9.

M. Szkulmowski, A. Szkulmowska, T. Bajraszewski, A. Kowalczyk, and M. Wojtkowski, “Flow velocity estimation using joint spectral and time domain optical coherence tomography,” Opt. Express 16(9), 6008–6025 (2008). [CrossRef] [PubMed]

10.

A. Szkulmowska, M. Szkulmowski, D. Szlag, A. Kowalczyk, and M. Wojtkowski, “Three-dimensional quantitative imaging of retinal and choroidal blood flow velocity using joint spectral and time domain optical coherence tomography,” Opt. Express 17(13), 10584–10598 (2009). [CrossRef] [PubMed]

11.

I. Grulkowski, I. Gorczynska, M. Szkulmowski, D. Szlag, A. Szkulmowska, R. A. Leitgeb, A. Kowalczyk, and M. Wojtkowski, “Scanning protocols dedicated to smart velocity ranging in spectral OCT,” Opt. Express 17(26), 23736–23754 (2009). [CrossRef]

12.

A. Mariampillai, B. A. Standish, E. H. Moriyama, M. Khurana, N. R. Munce, M. K. K. Leung, J. Jiang, A. Cable, B. C. Wilson, I. A. Vitkin, and V. X. D. Yang, “Speckle variance detection of microvasculature using swept-source optical coherence tomography,” Opt. Lett. 33(13), 1530–1532 (2008). [CrossRef] [PubMed]

13.

J. Fingler, D. Schwartz, C. Yang, and S. E. Fraser, “Mobility and transverse flow visualization using phase variance contrast with spectral domain optical coherence tomography,” Opt. Express 15(20), 12636–12653 (2007). [CrossRef] [PubMed]

14.

Y. K. Tao, A. M. Davis, and J. A. Izatt, “Single-pass volumetric bidirectional blood flow imaging spectral domain optical coherence tomography using a modified Hilbert transform,” Opt. Express 16(16), 12350–12361 (2008). [CrossRef] [PubMed]

15.

Y. K. Tao, K. M. Kennedy, and J. A. Izatt, “Velocity-resolved 3D retinal microvessel imaging using single-pass flow imaging spectral domain optical coherence tomography,” Opt. Express 17(5), 4177–4188 (2009). [CrossRef] [PubMed]

16.

R. K. Wang, S. L. Jacques, Z. Ma, S. Hurst, S. R. Hanson, and A. Gruber, “Three Dimensional Optical Angiography,” Opt. Express 15(7), 4083–4097 (2007). [CrossRef] [PubMed]

17.

R. K. Wang, “In vivo full range complex Fourier domain optical coherence tomography,” Appl. Phys. Lett. 90(5), 054103 (2007). [CrossRef]

18.

R. K. Wang, “Fourier domain optical coherence tomography achieves full range complex imaging in vivo by introducing a carrier frequency during scanning,” Phys. Med. Biol. 52(19), 5897–5907 (2007). [CrossRef] [PubMed]

19.

R. K. Wang and S. Hurst, “Mapping of cerebro-vascular blood perfusion in mice with skin and skull intact by Optical Micro-AngioGraphy at 1.3 mum wavelength,” Opt. Express 15(18), 11402–11412 (2007). [CrossRef] [PubMed]

20.

R. K. Wang and L. An, “Doppler optical micro-angiography for volumetric imaging of vascular perfusion in vivo,” Opt. Express 17(11), 8926–8940 (2009). [CrossRef] [PubMed]

21.

L. An and R. K. Wang, “In vivo volumetric imaging of vascular perfusion within human retina and choroids with optical micro-angiography,” Opt. Express 16(15), 11438–11452 (2008). [CrossRef] [PubMed]

22.

B. J. Vakoc, S. H. Yun, J. F. de Boer, G. J. Tearney, and B. E. Bouma, “Phase-resolved optical frequency domain imaging,” Opt. Express 13(14), 5483–5493 (2005). [CrossRef] [PubMed]

23.

H. W. Ren, T. Sun, D. J. MacDonald, M. J. Cobb, and X. D. Li, “Real-time in vivo blood-flow imaging by moving-scatterer-sensitive spectral-domain optical Doppler tomography,” Opt. Lett. 31(7), 927–929 (2006). [CrossRef] [PubMed]

24.

H. Ren and X. Li, “Clutter rejection filters for optical Doppler tomography,” Opt. Express 14(13), 6103–6112 (2006). [CrossRef] [PubMed]

25.

I. M. Braverman, “The Cutaneous Microcirculation,” J. Investig. Dermatol. Symp. Proc. 5(1), 3–9 (2000). [CrossRef]

ToC Category:
Medical Optics and Biotechnology

History
Original Manuscript: December 10, 2009
Revised Manuscript: March 10, 2010
Manuscript Accepted: March 12, 2010
Published: April 5, 2010

Virtual Issues
Vol. 5, Iss. 8 Virtual Journal for Biomedical Optics

Citation
Lin An, Jia Qin, and Ruikang K Wang, "Ultrahigh sensitive optical microangiography for in vivo imaging of microcirculations within human skin tissue beds," Opt. Express 18, 8220-8228 (2010)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=oe-18-8-8220


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References

  1. M. Stücker, V. Baier, T. Reuther, K. Hoffmann, K. Kellam, and P. Altmeyer, “Capillary blood cell velocity in human skin capillaries located perpendicularly to the skin surface: measured by a new laser Doppler anemometer,” Microvasc. Res. 52(2), 188–192 (1996). [CrossRef] [PubMed]
  2. J. D. Briers, “Laser Doppler, speckle and related techniques for blood perfusion mapping and imaging,” Physiol. Meas. 22(4), 201 (2001). [CrossRef]
  3. H. F. Zhang, K. Maslov, G. Stoica, and L. V. Wang, “Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging,” Nat. Biotechnol. 24(7), 848–851 (2006). [CrossRef] [PubMed]
  4. A. F. Fercher, W. Drexler, C. K. Hitzenberger, and T. Lasser, “Optical coherence tomography – principles and applications,” Rep. Prog. Phys. 66(2), 239–303 (2003). [CrossRef]
  5. P. H. Tomlins and R. K. Wang, “Theory, development and applications of optical coherence tomography,” J. Phys. D Appl. Phys. 38(15), 2519–2535 (2005). [CrossRef]
  6. Y. H. Zhao, Z. P. Chen, Z. H. Ding, H. Ren, and J. S. Nelson, “Real-time phase-resolved functional optical coherence tomography by use of optical Hilbert transformation,” Opt. Lett. 27(2), 98–100 (2002). [CrossRef]
  7. B. J. Vakoc, R. M. Lanning, J. A. Tyrrell, T. P. Padera, L. A. Bartlett, T. Stylianopoulos, L. L. Munn, G. J. Tearney, D. Fukumura, R. K. Jain, and B. E. Bouma, “Three-dimensional microscopy of the tumor microenvironment in vivo using optical frequency domain imaging,” Nat. Med. 15(10), 1219–1223 (2009). [CrossRef] [PubMed]
  8. A. H. Bachmann, M. L. Villiger, C. Blatter, T. Lasser, and R. A. Leitgeb, “Resonant Doppler flow imaging and optical vivisection of retinal blood vessels,” Opt. Express 15(2), 408–422 (2007). [CrossRef] [PubMed]
  9. M. Szkulmowski, A. Szkulmowska, T. Bajraszewski, A. Kowalczyk, and M. Wojtkowski, “Flow velocity estimation using joint spectral and time domain optical coherence tomography,” Opt. Express 16(9), 6008–6025 (2008). [CrossRef] [PubMed]
  10. A. Szkulmowska, M. Szkulmowski, D. Szlag, A. Kowalczyk, and M. Wojtkowski, “Three-dimensional quantitative imaging of retinal and choroidal blood flow velocity using joint spectral and time domain optical coherence tomography,” Opt. Express 17(13), 10584–10598 (2009). [CrossRef] [PubMed]
  11. I. Grulkowski, I. Gorczynska, M. Szkulmowski, D. Szlag, A. Szkulmowska, R. A. Leitgeb, A. Kowalczyk, and M. Wojtkowski, “Scanning protocols dedicated to smart velocity ranging in spectral OCT,” Opt. Express 17(26), 23736–23754 (2009). [CrossRef]
  12. A. Mariampillai, B. A. Standish, E. H. Moriyama, M. Khurana, N. R. Munce, M. K. K. Leung, J. Jiang, A. Cable, B. C. Wilson, I. A. Vitkin, and V. X. D. Yang, “Speckle variance detection of microvasculature using swept-source optical coherence tomography,” Opt. Lett. 33(13), 1530–1532 (2008). [CrossRef] [PubMed]
  13. J. Fingler, D. Schwartz, C. Yang, and S. E. Fraser, “Mobility and transverse flow visualization using phase variance contrast with spectral domain optical coherence tomography,” Opt. Express 15(20), 12636–12653 (2007). [CrossRef] [PubMed]
  14. Y. K. Tao, A. M. Davis, and J. A. Izatt, “Single-pass volumetric bidirectional blood flow imaging spectral domain optical coherence tomography using a modified Hilbert transform,” Opt. Express 16(16), 12350–12361 (2008). [CrossRef] [PubMed]
  15. Y. K. Tao, K. M. Kennedy, and J. A. Izatt, “Velocity-resolved 3D retinal microvessel imaging using single-pass flow imaging spectral domain optical coherence tomography,” Opt. Express 17(5), 4177–4188 (2009). [CrossRef] [PubMed]
  16. R. K. Wang, S. L. Jacques, Z. Ma, S. Hurst, S. R. Hanson, and A. Gruber, “Three Dimensional Optical Angiography,” Opt. Express 15(7), 4083–4097 (2007). [CrossRef] [PubMed]
  17. R. K. Wang, “In vivo full range complex Fourier domain optical coherence tomography,” Appl. Phys. Lett. 90(5), 054103 (2007). [CrossRef]
  18. R. K. Wang, “Fourier domain optical coherence tomography achieves full range complex imaging in vivo by introducing a carrier frequency during scanning,” Phys. Med. Biol. 52(19), 5897–5907 (2007). [CrossRef] [PubMed]
  19. R. K. Wang and S. Hurst, “Mapping of cerebro-vascular blood perfusion in mice with skin and skull intact by Optical Micro-AngioGraphy at 1.3 mum wavelength,” Opt. Express 15(18), 11402–11412 (2007). [CrossRef] [PubMed]
  20. R. K. Wang and L. An, “Doppler optical micro-angiography for volumetric imaging of vascular perfusion in vivo,” Opt. Express 17(11), 8926–8940 (2009). [CrossRef] [PubMed]
  21. L. An and R. K. Wang, “In vivo volumetric imaging of vascular perfusion within human retina and choroids with optical micro-angiography,” Opt. Express 16(15), 11438–11452 (2008). [CrossRef] [PubMed]
  22. B. J. Vakoc, S. H. Yun, J. F. de Boer, G. J. Tearney, and B. E. Bouma, “Phase-resolved optical frequency domain imaging,” Opt. Express 13(14), 5483–5493 (2005). [CrossRef] [PubMed]
  23. H. W. Ren, T. Sun, D. J. MacDonald, M. J. Cobb, and X. D. Li, “Real-time in vivo blood-flow imaging by moving-scatterer-sensitive spectral-domain optical Doppler tomography,” Opt. Lett. 31(7), 927–929 (2006). [CrossRef] [PubMed]
  24. H. Ren and X. Li, “Clutter rejection filters for optical Doppler tomography,” Opt. Express 14(13), 6103–6112 (2006). [CrossRef] [PubMed]
  25. I. M. Braverman, “The Cutaneous Microcirculation,” J. Investig. Dermatol. Symp. Proc. 5(1), 3–9 (2000). [CrossRef]

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