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Virtual Journal for Biomedical Optics

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  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 7, Iss. 2 — Feb. 1, 2012
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Motion-insensitive optical coherence tomography based micro-angiography

Ting-Ta Chi, Cheng-Kuang Lee, Chiung-Ting Wu, Chih-Chung Yang, Meng-Tsan Tsai, and Chun-Ping Chiang  »View Author Affiliations


Optics Express, Vol. 19, Issue 27, pp. 26117-26131 (2011)
http://dx.doi.org/10.1364/OE.19.026117


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Abstract

An improved image processing procedure for suppressing the phase noise due to a motion artifact acquired during optical coherence tomography scanning and effectively illustrating the blood vessel distribution in a living tissue is demonstrated. This new processing procedure and the widely used procedure for micro-angiography application are based on the selection of high-frequency components in the spatial-frequency spectrum of B-mode scanning (x-space), which are contributed from the image portions of moving objects. However, by switching the processing order between the x-space and k-space, the new processing procedure shows the superior function of effectively suppressing the phase noise due to a motion artifact. After the blood vessel positions are precisely acquired based on the new processing procedure, the projected blood flow speed can be more accurately calibrated based on a previously reported method. The demonstrated new procedure is useful for clinical micro-angiography application, in which a stepping motor of generating motion artifacts is usually used in the scanning probe.

© 2011 OSA

1. Introduction

In this paper, we demonstrate an alternative imaging processing procedure for effectively suppressing the high-frequency phase noise due to a motion artifact. The basic concept of the proposed image processing procedure is similar to the OMAG technique. However, the image processing procedure is modified. With this new procedure, we can effectively suppress the phase noise due to the scanning nature of a stepping motor, which is widely used for building an OCT scanning probe. Such a probe has been used for scanning oral cavity to early diagnose oral cancer and precancer [19

19. M. T. Tsai, C. K. Lee, H. C. Lee, H. M. Chen, C. P. Chiang, Y. M. Wang, and C. C. Yang, “Differentiating oral lesions in different carcinogenesis stages with optical coherence tomography,” J. Biomed. Opt. 14(4), 044028 (2009). [CrossRef] [PubMed]

, 20

20. C. C. Yang, 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]

]. Although the method of subtracting the maximum-count phase shift in each A-mode scan has been reported for suppressing the phase noise due to motion artifacts [12

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

], in this paper, we illustrate the problem of using this method when the blood vessel distribution covers a large cross section in an OCT image. We will show that by using our processing procedure for obtaining the micro-angiography information in advance, we can better use the maximum-count phase-shift method for acquiring more accurate ODT results. In section 2 of this paper, the used OCT systems for in vivo scanning and the basic scanning results are shown. The theory behind our approach is discussed in section 3. Then, the processed images and their comparisons with those based on the conventional techniques are presented in section 4. Finally, conclusions are drawn in section 5.

2. Optical coherence tomography systems and scanning results

Figure 1(a)
Fig. 1 (a) Setup of the two SS-OCT systems. In the sample arm, one of the systems is connected with a scanning probe with its layout shown in part (b) and the other system is connected with a scanning galvanometer setup as shown in part (c).
shows the common setup of the two used swept-source OCT (SS-OCT) systems in this study. In the setup, besides the fiber Mach-Zehnder interferometer to form the major body of the OCT system, 5% of the light source power is sent to a fiber Bragg grating through a circulator for synchronizing the OCT signal acquisition with the frequency sweeping of the swept source [21

21. R. K. Manapuram, V. G. R. Manne, and K. V. Larin, “Development of phase-stabilized swept-source OCT for the ultrasensitive quantification of microbubbles,” Laser Phys. 18(9), 1080–1086 (2008). [CrossRef]

]. The interfered spectral signals are monitored by a balanced detector (Thorlabs, PDB12A) and acquired by a personal computer (PC) through a data acquisition (DAQ) card (National Instruments, PCI-5122 or PXIe-5122). All the fiber couplers and circulators in the systems are manufactured by the company of Thorlabs. In the sample arm, one of the OCT systems is connected to a scanning probe containing a stepping motor. The other is connected to a scanning galvanometer. In the OCT system with the scanning probe, the swept source has a sweeping wavelength range of 110 nm (Santec, HSL2000). In the other OCT system with the scanning galvanometer, the swept source has a sweeping wavelength range of 170 nm (Santec, HSL2100). The central wavelength and scanning rate of both light sources are 1310 nm and 20 kHz, respectively. The fiber Bragg grating (Lead Fiber Optics Co.) used in the OCT system of probe scanning has the Bragg wavelength at 1260 nm. That used (also Lead Fiber Optics Co.) in the OCT system of galvanometer scanning has the Bragg wavelength at 1230 nm. Figure 1(b) shows the schematic drawing of the scanning probe. Here, the linear stepping motor (Montrol System Co., A35H4N-24) controls the translational motion of the probe shaft for B-mode scan to achieve a scanning speed of 10 cm/s and a 1 cm scanning length. However, in this study, we use the scanning speed of only 1.25 cm/s with a B-mode scanning range of 1.25 mm. The probe has a length of 10 cm beyond the stepping motor at the proximal end. The square geometry of the probe cross section has the dimension of 0.8 cm. At the distal end of the probe, an opening of 2.5 cm x 0.5 cm is fabricated for light illumination onto a sample and backscattered light collection. The illuminating light beam is focused by a Grin lens (OZ Optics) at the fiber end. Its propagation direction is changed by the reflection of a prism mirror (OZ Optics) inside the probe. Figure 1(c) shows the setup of the galvanometer scanning unit. In this setup, the light beam is swung for B-mode scan through the reflection by a mirror mounted on a galvanometer (Thorlabs, GVS002). The swung light beam is then focused by an objective lens (Mitutoyo, Q73014308A) for illuminating a sample. The OCT system with the scanning probe has been used for clinical scanning of oral cancer patients in a hospital and has led to the discovery of several effective indicators for the diagnoses of oral cancer and precancer [19

19. M. T. Tsai, C. K. Lee, H. C. Lee, H. M. Chen, C. P. Chiang, Y. M. Wang, and C. C. Yang, “Differentiating oral lesions in different carcinogenesis stages with optical coherence tomography,” J. Biomed. Opt. 14(4), 044028 (2009). [CrossRef] [PubMed]

, 20

20. C. C. Yang, 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]

]. It is noted that in fabricating a scanning probe for clinical application, optical micro-electro-mechanical systems (MEMSs) have been used for two-dimensional or three-dimensional lateral scans [22

22. J. Sun, S. Guo, L. Wu, L. Liu, S. W. Choe, B. S. Sorg, and H. Xie, “3D in vivo optical coherence tomography based on a low-voltage, large-scan-range 2D MEMS mirror,” Opt. Express 18(12), 12065–12075 (2010). [CrossRef] [PubMed]

, 23

23. K. H. Kim, B. H. Park, G. N. Maguluri, T. W. Lee, F. J. Rogomentich, M. G. Bancu, B. E. Bouma, J. F. de Boer, and J. J. Bernstein, “Two-axis magnetically-driven MEMS scanning catheter for endoscopic high-speed optical coherence tomography,” Opt. Express 15(26), 18130–18140 (2007). [CrossRef] [PubMed]

]. However, the MEMS technology does not seem mature enough for the application of fabricating OCT scanning probes. In practice, a stepping motor is still one of the most reliable components for B-mode scanning of a probe. However, because of the stepping motion nature of such a component, quasi-periodical phase noise is added to OCT signal during the B-mode scan.

3. Theory

The basic idea for mapping the blood vessel distribution relies on the faster time-resolved variation of OCT signal at those pixels with object motions. When the B-mode scan pixel size is small enough, the lateral variation of OCT intensity signal at a location of object motion will show a feature of higher spatial frequency, when compared with other locations of static structures. In this situation, the high-frequency components of a spatial-frequency spectrum, obtained after a Fourier transform of the OCT intensity signal along the B-mode scan direction, correspond to the contributions from those locations of object motions. A reasonable selection of the high-frequency components of the spatial-frequency spectrum can provide us with the blood vessel mapping after an inverse Fourier transform. This basic concept has been used in the OMAG technique. However, this technique becomes less effective when the condition of motion artifact or phase noise like the case shown in Fig. 2(b) is encountered. To demonstrate such a situation, we use the OCT system with galvanometer scanning to scan human skin on one of the fingers of a volunteer. During the scanning, the volunteer intentionally moved the finger to produce a motion artifact. Figures 4(a)
Fig. 4 (a) OCT structure image of human skin on a finger of a volunteer obtained with galvanometer scanning. (b) Phase shift mapping of the OCT image of part (a) obtained by evaluating the phase difference between two neighboring A-mode scans. The phase noise in the right portion is caused by an intentional motion of the finger. The arrow indicates a blood vessel, which can be seen through the phase shift evaluation. The other blood vessel is blurred by the phase noise.
and 4(b) show the OCT structure image and its phase shift mapping, respectively. The image in Fig. 4(a) consists of 285 and 1250 pixels in the A- and B-mode scan directions, respectively. Although the effect of the motion artifact cannot be identified in the structure image, it can be clearly observed in the phase shift mapping. In Fig. 4(b), a signal feature, indicated by the arrow, corresponding to a blood vessel, can be clearly observed. The phase noise caused by finger motion can be seen in the right portion. Such phase noise masks another blood vessel feature, as to be seen in the following discussion.

The different lateral signal variations between the image locations of moving objects and static structures can be seen in Figs. 5(a)
Fig. 5 (a) Duplicate of Fig. 4(a) with the portion circled by the dashed square being magnified to give part (b). The upper (red) and lower (blue) horizontal dashed line scan profiles are shown in parts (c) and (d), respectively.
-5(d). Here, Fig. 5(a) duplicates Fig. 4(a) with a rectangular region (circled by the green dashed lines) being magnified to give Fig. 5(b). Near the center of Fig. 5(b), one can see a region of fast signal variation along the lateral direction. By plotting a horizontal blue dashed line to pass this region and a red dashed line above it (outside this region) in Fig. 5(b), one can clearly see the different lateral variations in their line-scan profiles, as demonstrated in Figs. 5(c) and 5(d) for the upper (red) and lower (blue) line scans, respectively. Here, one can see that in the lateral range x between 40 and 110 μm of Fig. 5(d), the signal variation is faster than those outside this x range and all the x range in Fig. 5(c). The fast signal variation is caused by the blood cell motion in the blood vessel leading to structure changes with time. Therefore, in successive A-mode scans, fast-varying backscattering signals are recorded. The portion of fast variation in Fig. 5(d) contributes to the high-frequency components in the lateral spatial-frequency spectrum. The selection of those high-frequency components for inverse Fourier transform can provide us with blood vessel image.

Mathematically, if we start with the real interfered spectral signals collected by an OCT system at a particular depth zl, A(k, zl, x), and assume that there is no motion artifact or phase noise, the image processing procedure in the OMAG technique for obtaining the blood vessel distribution signal, B(zl, x), is as follows:

B(zl,x)=Abs{S[Fk(Fx1{W[Fx(A(k,zl,x))]})]}.
(1)

Here, Fx and Fx1 represent the Fourier transform and inverse Fourier transform, respectively, along the x direction. The notation, Fk, stands for the Fourier transform in the k domain (frequency). Also, the notation W denotes a window function for deleting the low-frequency components in both real and imaginary parts of the spatial-frequency spectrum. Meanwhile, S represents the mirror image suppression operation. In addition, Abs stands for the mathematical operation of taking the absolute value. It is noted that z and x have been used for denoting the coordinates in the A- and B-mode scanning directions, respectively. The image processing procedure described in Eq. (1) (referred to as the reference procedure) has been widely used for micro-angiography applications. However, it is difficult to obtain clear blood vessel distributions based on this procedure when motion artifacts exist. A motion artifact can usually produce phase noise, ϕ(zl, x), in A(k, zl, x) with laterally high-spatial-frequency components. In this situation, the OCT signal can be expressed as

A(k,zl,x)=a(zl,x)cos[kzl+ϕ(zl,x)].
(2)

Here, a(zl, x) stands for the backscattering signal from the location of (zl, x). The phase noise cannot be removed in the whole mathematical operation procedure in Eq. (1) such that it may blur the blood vessel image. Nevertheless, a change of the mathematical operation procedure in Eq. (1) can help in deleting the phase noise.

Our proposed image processing procedure is as follows:

B(zl,x)=Abs(Fx1{W[Fx(Abs{S[Fk(A(k,zl,x))]})]}).
(3)

Here, after the mirror image suppression operation (S), the absolute-value signal becomes

Abs(Fk{a(zl,x)exp[ikzl+iϕ(zl,x)]})=Abs{a(zl,x)exp[iϕ(zl,x)]δ(zzl)}=a(zl,x)δ(zzl).
(4)

Therefore, the phase noise is removed. However, in the reference procedure shown in Eq. (1), after the mirror image suppression operation (S), the absolute-value signal becomes

Abs(Fk{Fx1[W(Fx{a(zl,x)exp[ikzl+iϕ(zl,x)]})]})=Abs[Fk{exp(ikzl)[Fx1(W{Fx[a(zl,x)]Fx[exp(iϕ(zl,x))]})]}].
(5)

Here, the notation stands for a convolution operation. With the convolution operation and window function, the phase noise cannot be suppressed even after we take the absolute value. Therefore, with the reference processing procedure, the phase noise will blur the blood vessel image. It is noted that if ϕ(zl, x) represents a constant phase shift, which is commonly used in ODT, it can be deleted through the reference procedure. Also, if the motion artifact produces only the phase noise of low spatial frequency components, it can be suppressed by the window function. In this situation, the reference processing procedure should also work well for suppressing the phase noise.

4. Scanning and processing results

Figures 6(a)
Fig. 6 (a) and (b): Processed results of blood vessel distribution based on our procedure and the reference procedure, respectively, from the scanning result shown in Fig. 4(a).
and 6(b) show the processed results, i.e., B(zl, x), based on our procedure and the reference procedure, respectively, of the scanning result shown in Fig. 4(a). Here, one can see that with our processing procedure, two blood vessels can be clearly seen, as indicated by the arrows. However, with the reference processing procedure, the blood vessel on the right is masked by the vertical stripes caused by the intentionally produced motion artifact. Similar comparison can be seen in Figs. 7(a)
Fig. 7 (a) and (b): Processed results of blood vessel distribution based on our procedure and the reference procedure, respectively, from the scanning result shown in Fig. 2(a).
and 7(b), which show the processed results based on our procedure and the reference procedure, respectively, of the mucosa image in Fig. 2(a). Again, our processing procedure is superior to the reference one in acquiring the blood vessel distribution. At least six blood vessels can be identified in Fig. 7(a), as indicated by arrows and circles. It is noted that if the phase noise distributions in Fig. 2(b) and 4(b) can be effectively suppressed, say, through the method of subtracting the maximum-count phase shift in each A-mode scan, the reference procedure can also be used for obtaining clear blood vessel mapping. However, as far as the micro-angiography application is concerned, the required extra work of suppressing the phase noise due to motion artifacts before applying the reference image processing procedure represents a drawback. Actually, after suppressing the phase noise, we can obtain the ODT image. The ODT image contains the information of blood vessel distribution (micro-angiography) and projected blood flow speed. The suppressions of phase noise and the ODT image illustrations of the OCT results in Figs. 2 and 4 will be discussed later with Figs. 8
Fig. 8 (a) Duplicate of Fig. 6(a) with three selections of different A-mode scan depth ranges as I, II, and III. The ODT images based on selected ranges I, II, and III are shown in parts (b), (c), and (d), respectively. The speed scale coding is shown at the bottom.
-11
Fig. 11 (a)-(c): Line-scan profiles of projected blood flow speed along the dashed lines in Figs. 10(b)-10(d), respectively. The spiky curves (Data) show the results in Figs. 10(b)-10(d). The smoother curves (Fitting) are obtained after the high spatial-frequency components are filtered. The arrows indicate the locations of the two blood vessels.
.

The comparisons of ODT results between different selected depth ranges, similar to those in Figs. 8(b)-8(d), corresponding to the OCT scanning result in Fig. 2(a) are demonstrated in Figs. 10(b)
Fig. 10 (a) Duplicate of Fig. 7(a) with three selections of different A-mode scan depth ranges as I, II, and III. The ODT images based on selected ranges I, II, and III are shown in parts (b), (c), and (d), respectively. The speed scale coding is shown at the right end.
-10(d). Again, the comparisons show that the selection of a large depth range for searching the phase shift value of maximum counts is useful for suppressing the phase noise due to a motion artifact. The line-scan profiles of projected blood flow speed along the horizontal dashed lines in Figs. 10(b)-10(d) are plotted to give the spiky (red) curves (labeled by “Data”) in Figs. 11(a)-11(c), respectively. Similar to those in Figs. 9(a)-9(c), a smoother curve (labeled by “Fitting”) is plotted after the high spatial-frequency components are filtered in each of Figs. 11(a)-11(c). Here, one can again see that when the phase noise is not completely suppressed, the evaluated flow speed is reduced.

To show that the condition of large blood vessel cross section in Fig. 12 is often encountered, in Figs. 15
Fig. 15 (a) Another OCT structure image of human skin on a finger of a volunteer obtained with probe scanning. (b) Phase shift mapping of the OCT image of part (a) obtained by evaluating the phase difference between two neighboring A-mode scans. Processed results of blood vessel distribution based on our procedure and the reference procedure from the scanning result shown in part (a) are illustrated in parts (c) and (d), respectively.
-17
Fig. 17 (a) and (b): Line-scan profiles of projected blood flow speed along the dashed lines in Figs. 16(b) and 16(c), respectively. The spiky curves (Data) show the results in Figs. 16(b) and 16(c). The smoother curves (Fitting) are obtained after the high spatial-frequency components are filtered. The arrows indicate the locations of the blood vessels.
, we show another case of human skin scan with the probe-connected OCT system. Figures 15-17 are similar to Figs. 12-14, respectively. As shown in Fig. 15(c), a blood vessel cluster can be seen in the lower-right corner of the image. With the large cross section of blood vessel distribution, if the depth range selected for searching the maximum-count phase shift covers the blood vessel cluster (range II in Fig. 16(a)
Fig. 16 (a) Duplicate of Fig. 15(c) with two selections of different A-mode scan depth ranges as I and II. The ODT images based on selected ranges I and II are shown in parts (b) and (c), respectively. The speed scale coding is shown at the bottom.
), the phase noise suppression becomes quite poor, as shown in Fig. 16(c). In this situation, the blood flow speed can be underestimated, as demonstrated in Fig. 17(b), when compared with Fig. 17(a).

5. Conclusions

In summary, we have demonstrated a different image processing procedure for suppressing the phase noise due to a motion artifact acquired during OCT scanning and effectively illustrating the blood vessel distribution in a living tissue. Although both our processing procedure and the widely used procedure (the reference procedure) for micro-angiography application were based on the same concept of selecting the high-frequency components in the spatial-frequency spectrum of B-mode scanning (x-space), by switching the processing order between the x- and k-space, our processing procedure could effectively suppress the phase noise due to a motion artifact. After the blood vessel positions were accurately determined, high-quality ODT images could be obtained with a more careful calibration based on a previously reported method. Our new procedure is useful for clinical micro-angiography application, in which a stepping motor of generating motion artifacts is usually used in the scanning probe.

Acknowledgment

This research was supported by National Science Council and National Health Research Institute, The Republic of China, under the grants of NSC 99-2218-E-002-013, NSC 99-3114-B-002-005, and NHRI-EX100-10043EI.

References and links

1.

Z. P. Chen, T. E. Milner, D. Dave, and J. S. Nelson, “Optical Doppler tomographic imaging of fluid flow velocity in highly scattering media,” Opt. Lett. 22(1), 64–66 (1997). [CrossRef] [PubMed]

2.

J. Zhang and Z. P. Chen, “In vivo blood flow imaging by a swept laser source based Fourier domain optical Doppler tomography,” Opt. Express 13(19), 7449–7457 (2005). [CrossRef] [PubMed]

3.

Z. Chen, T. E. Milner, S. Srinivas, X. Wang, A. Malekafzali, M.J.C. van Gemert, and J. S. Nelson, “Noninvasive imaging of in vivo blood flow velocity using optical Doppler tomography,” Opt. Lett. 22(14), 1119–1121 (1997). [CrossRef] [PubMed]

4.

Y. Zhao, Z. P. Chen, C. Saxer, S. Xiang, J. F. de Boer, and J. S. Nelson, “Phase-resolved optical coherence tomography and optical Doppler tomography for imaging blood flow in human skin with fast scanning speed and high velocity sensitivity,” Opt. Lett. 25(2), 114–116 (2000). [CrossRef] [PubMed]

5.

J. A. Izatt, M. D. Kulkarni, S. Yazdanfar, J. K. Barton, and A. J. Welch, “In vivo bidirectional color Doppler flow imaging of picoliter blood volumes using optical coherence tomography,” Opt. Lett. 22(18), 1439–1441 (1997). [CrossRef] [PubMed]

6.

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]

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B. Baumann, B. Potsaid, M. F. Kraus, J. J. Liu, D. Huang, J. Hornegger, A. E. Cable, J. S. Duker, and J. G. Fujimoto, “Total retinal blood flow measurement with ultrahigh speed swept source/Fourier domain OCT,” Biomed. Opt. Express 2(6), 1539–1552 (2011). [CrossRef] [PubMed]

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Z. Zhi, W. Cepurna, E. Johnson, T. Shen, J. Morrison, and R. K. Wang, “Volumetric and quantitative imaging of retinal blood flow in rats with optical microangiography,” Biomed. Opt. Express 2(3), 579–591 (2011). [CrossRef] [PubMed]

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F. Jaillon, S. Makita, E. J. Min, B. H. Lee, and Y. Yasuno, “Enhanced imaging of choroidal vasculature by high-penetration and dual-velocity optical coherence angiography,” Biomed. Opt. Express 2(5), 1147–1158 (2011). [CrossRef] [PubMed]

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B. A. Standish, K. K. C. Lee, X. Jin, A. Mariampillai, N. R. Munce, M. F. G. Wood, B. C. Wilson, I. A. Vitkin, and V. X. D. Yang, “Interstitial Doppler optical coherence tomography as a local tumor necrosis predictor in photodynamic therapy of prostatic carcinoma: an in vivo study,” Cancer Res. 68(23), 9987–9995 (2008). [CrossRef] [PubMed]

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Y. Wang, A. Fawzi, O. Tan, J. Gil-Flamer, and D. Huang, “Retinal blood flow detection in diabetic patients by Doppler Fourier domain optical coherence tomography,” Opt. Express 17(5), 4061–4073 (2009). [CrossRef] [PubMed]

12.

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

13.

R. K. Wang and Z. Ma, “Real-time flow imaging by removing texture pattern artifacts in spectral-domain optical Doppler tomography,” Opt. Lett. 31(20), 3001–3003 (2006). [CrossRef] [PubMed]

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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]

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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]

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L. An, H. M. Subhush, D. J. Wilson, and R. K. Wang, “High-resolution wide-field imaging of retinal and choroidal blood perfusion with optical microangiography,” J. Biomed. Opt. 15(2), 026011 (2010). [CrossRef] [PubMed]

17.

Z. Zhi, Y. Jung, Y. Jia, L. An, and R. K. Wang, “Highly sensitive imaging of renal microcirculation in vivo using ultrahigh sensitive optical microangiography,” Biomed. Opt. Express 2(5), 1059–1068 (2011). [CrossRef] [PubMed]

18.

L. An and R. K. Wang, “Full range complex ultrahigh sensitive optical microangiography,” Opt. Lett. 36(6), 831–833 (2011). [CrossRef] [PubMed]

19.

M. T. Tsai, C. K. Lee, H. C. Lee, H. M. Chen, C. P. Chiang, Y. M. Wang, and C. C. Yang, “Differentiating oral lesions in different carcinogenesis stages with optical coherence tomography,” J. Biomed. Opt. 14(4), 044028 (2009). [CrossRef] [PubMed]

20.

C. C. Yang, 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]

21.

R. K. Manapuram, V. G. R. Manne, and K. V. Larin, “Development of phase-stabilized swept-source OCT for the ultrasensitive quantification of microbubbles,” Laser Phys. 18(9), 1080–1086 (2008). [CrossRef]

22.

J. Sun, S. Guo, L. Wu, L. Liu, S. W. Choe, B. S. Sorg, and H. Xie, “3D in vivo optical coherence tomography based on a low-voltage, large-scan-range 2D MEMS mirror,” Opt. Express 18(12), 12065–12075 (2010). [CrossRef] [PubMed]

23.

K. H. Kim, B. H. Park, G. N. Maguluri, T. W. Lee, F. J. Rogomentich, M. G. Bancu, B. E. Bouma, J. F. de Boer, and J. J. Bernstein, “Two-axis magnetically-driven MEMS scanning catheter for endoscopic high-speed optical coherence tomography,” Opt. Express 15(26), 18130–18140 (2007). [CrossRef] [PubMed]

OCIS Codes
(110.4500) Imaging systems : Optical coherence tomography
(170.3880) Medical optics and biotechnology : Medical and biological imaging

ToC Category:
Medical Optics and Biotechnology

History
Original Manuscript: August 3, 2011
Revised Manuscript: October 6, 2011
Manuscript Accepted: November 20, 2011
Published: December 7, 2011

Virtual Issues
Vol. 7, Iss. 2 Virtual Journal for Biomedical Optics

Citation
Ting-Ta Chi, Cheng-Kuang Lee, Chiung-Ting Wu, Chih-Chung Yang, Meng-Tsan Tsai, and Chun-Ping Chiang, "Motion-insensitive optical coherence tomography based micro-angiography," Opt. Express 19, 26117-26131 (2011)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=oe-19-27-26117


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References

  1. Z. P. Chen, T. E. Milner, D. Dave, and J. S. Nelson, “Optical Doppler tomographic imaging of fluid flow velocity in highly scattering media,” Opt. Lett.22(1), 64–66 (1997). [CrossRef] [PubMed]
  2. J. Zhang and Z. P. Chen, “In vivo blood flow imaging by a swept laser source based Fourier domain optical Doppler tomography,” Opt. Express13(19), 7449–7457 (2005). [CrossRef] [PubMed]
  3. Z. Chen, T. E. Milner, S. Srinivas, X. Wang, A. Malekafzali, M.J.C. van Gemert, and J. S. Nelson, “Noninvasive imaging of in vivo blood flow velocity using optical Doppler tomography,” Opt. Lett.22(14), 1119–1121 (1997). [CrossRef] [PubMed]
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