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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. 4, Iss. 5 — May. 5, 2009
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Cellular resolution volumetric in vivo retinal imaging with adaptive optics–optical coherence tomography

Robert J. Zawadzki, Stacey S. Choi, Alfred R. Fuller, Julia W. Evans, Bernd Hamann, and John S. Werner  »View Author Affiliations


Optics Express, Vol. 17, Issue 5, pp. 4084-4094 (2009)
http://dx.doi.org/10.1364/OE.17.004084


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Abstract

Ultrahigh-resolution adaptive optics–optical coherence tomography (UHR-AO-OCT) instrumentation allowing monochromatic and chromatic aberration correction was used for volumetric in vivo retinal imaging of various retinal structures including the macula and optic nerve head (ONH). Novel visualization methods that simplify AO-OCT data viewing are presented, and include co-registration of AO-OCT volumes with fundus photography and stitching of multiple AO-OCT sub-volumes to create a large field of view (FOV) high-resolution volume. Additionally, we explored the utility of Interactive Science Publishing by linking all presented AO-OCT datasets with the OSA ISP software.

© 2009 Optical Society of America

Data sets associated with this article are available at http://hdl.handle.net/10376/1411. Links such as View 1 that appear in figure captions and elsewhere will launch custom data views if ISP software is present.

1. Introduction

Enabled by recent progress in the development of optical coherence tomography (OCT) [1–4

1. D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Flotte, K. Gregory, and C. A. Puliafito, “Optical coherence tomography,” Science 254, 1178–1181 (1991). [CrossRef] [PubMed]

], including its Fourier/spectral-domain variation [5–11

5. A. F. Fercher, C. K. Hitzenberger, G. Kamp, and Y. Elzaiat, “Measurement of intraocular distances by backscattering spectral interferometry,” Opt. Commun. 117, 43–48 (1995). [CrossRef]

], several companies have introduced clinical OCT instruments for ophthalmic imaging. This has resulted in rapid growth of OCT use for monitoring progression and treatment of many retinal diseases in everyday clinical practice. What makes OCT so attractive is its high sensitivity (ability to measure weak backscattered signals), high acquisition speed (allowing volumetric imaging within seconds) and high axial resolution tomographic cross-sections. The retinal organization of similar cell types arranged in almost transparent horizontal layers is conducive to identification of pathogenesis imaged in vivo with this technique. The well-defined spatial organization of the retina also invites complex image processing, including quantitative analysis of segmented layers, and registration with other clinical imaging methods. With deeper penetration of the optic nerve head (ONH) it also permits a study of ganglion cell axons as they begin their projection to subcortical and cortical projection sites.

Lateral resolution in clinical OCT systems is, however, insufficient for imaging of individual cellular structures. To overcome this limitation one would have to increase lateral resolution by increasing the numerical aperture (NA) of the imaging system. This can be achieved by increasing the diameter of the OCT imaging beam at the eye’s pupil. Unfortunately due to imperfections in the optics of the eye, this approach yields only a small improvement in lateral resolution. For most subjects, if one increases the size of the imaging beam by over 2 mm at the eye’s pupil, lateral resolution deteriorates [12

12. W. J. Donnelly III and A. Roorda, “Optimal pupil size in the human eye for axial resolution,” J. Opt. Soc. Am. A 20, 2010–2015 (2003). [CrossRef]

]. Correcting ocular aberrations in real time can overcome this limitation and further improve lateral resolution. This can be achieved by implementing adaptive optics (AO) to measure and correct the wavefront error of the eye. The value of high-resolution, AO-based imaging has been demonstrated in fundus cameras (flood illuminated ophthalmoscopes) [13–15

13. J. Liang, D. R. Williams, and D. T. Miller, “Supernormal vision and high-resolution retinal imaging through adaptive optics,” J. Opt. Soc. Am. A 14, 2884–2892 (1997). [CrossRef]

] and scanning laser ophthalmoscopes [16–18

16. A. Roorda, F. Romero-Borja, W. J. Donnelly III, H. Queener, T. J. Hebert, and M. C. W. Campbell, “Adaptive optics scanning laser ophthalmoscopy,” Opt. Express 10, 405–412 (2002). [PubMed]

] to visualize cellular retinal structures. However, due to the limited axial resolution and sensitivity of these instruments, they have been mainly used in imaging highly reflective structures such as cone photoreceptors, micro-capillaries and nerve fiber bundles visualized over a narrow depth of focus without insight into axial structure. To overcome this limitation and to gain further insights into volumetric retinal features at cellular resolution, AO has been incorporated into various OCT systems [19–29

19. D. T. Miller, J. Qu, R. S. Jonnal, and K. Thorn, “Coherence gating and adaptive optics in the eye,” Proc. SPIE 4956, 65–72 (2003). [CrossRef]

]. However volumetric resolution and visibility of retinal details achieved by those instruments have been limited either by axial or lateral resolution. Recently, the first two papers reporting AO-OCT with isotropic volumetric resolution (~3 µm) [30–31

30. R. J. Zawadzki, B. Cense, Y. Zhang, S. S. Choi, D. T. Miller, and J. S. Werner, “Ultrahigh-resolution optical coherence tomography with monochromatic and chromatic aberration correction,” Opt. Express 16, 8126–8143 (2008). [CrossRef] [PubMed]

] have been published. To achieve this resolution, AO combined with ultrahigh-resolution (UHR)-OCT requires additional optical elements to compensate for the eye’s longitudinal chromatic aberration (LHA).

In this paper, we present for the first time volumetric images of various retinal structures acquired with the UC Davis UHR-AO-OCT system [30

30. R. J. Zawadzki, B. Cense, Y. Zhang, S. S. Choi, D. T. Miller, and J. S. Werner, “Ultrahigh-resolution optical coherence tomography with monochromatic and chromatic aberration correction,” Opt. Express 16, 8126–8143 (2008). [CrossRef] [PubMed]

] allowing monochromatic and chromatic aberration correction. Novel methods to simplify AO-OCT data visualization, including co-registration of AO-OCT volumes with fundus photography and stitching of multiple AO-OCT sub-volumes to create large field-of-view (FOV) high-resolution volumes are presented. Additionally, we have taken advantage of the OSA “Interactive Science Publishing” by linking all the presented AO-OCT datasets to make possible data visualization with OSA ISP software.

2. Materials and methods

2.1. UHR-AO-OCT instrument

The light source used for both UHR-OCT and wavefront sensing is a superluminescent diode (Superlum BroadLighter T840-HP). This permits ~3.5 µm axial resolution in retinal tissue. The measured light level at the entrance pupil of the subject’s eye is maintained below 450 µW. In our current configuration, the imaging beam diameter is approximately 6.6 mm at the subject’s pupil. An AO system using two deformable mirrors (DMs) for better AO performance, has been introduced into the OCT sample arm to allow correction of the subject’s ocular aberrations over this pupil size. With good AO correction, lateral resolution is similar to axial resolution, resulting in an isotropic volumetric point-spread function. The OCT-control unit drives vertical and horizontal scanners with programmable scanning patterns (maximum field of view of 4°), acquires ~18k lines/s for 50 µs line exposures (there is ~6 µs/line of read out and processing time) and displays 32 frames/s with 500 lines/frame of OCT data. An AO-control system operates the AO closed-loop correction at a rate of 16 Hz. The same light source is used for both wavefront sensing and imaging to permit the OCT data to be saved without interfering with the AO system operation. In the design of our AO-OCT sample arm, all key optical components were at planes conjugate to the pupil of the eye, including vertical and horizontal scanning mirrors, wavefront correctors (AOptix Technologies Bimorph DM and Boston Micromachines Corp. MEMS DM), the Hartmann-Shack wavefront sensor and the fiber collimator for light delivery.

2.2. Volumetric data acquisition

Several different 3D raster scanning modes have been used to acquire the images presented in this paper. In our standard sampling acquisition mode [100 B-scans (1000 lines/B-scan)], 100,000 A-lines are acquired in about T=5.5 s to image one volume. This grid is usually used to acquire “larger” AO-OCT volumes (1 mm × 1 mm) where equidistant lateral sampling is not critical (visualization of capillaries or nerve fiber bundles). An alternative commonly used sampling grid [300 B-scans (250 lines/B-scan)] has a shorter acquisition time, T=4.2 s. This grid is usually used to acquire “small” AO-OCT volumes (250 µm×300 µm) where equidistant lateral sampling is important (e.g., for visualization of cellular retinal structures such as photoreceptors). Unfortunately, despite head restraint and implementation of B-scan co-registration, it is not possible to correct all the distortions introduced by eye motion. This can be observed as disruptions in retinal vasculature on the OCT fundus image (that is created from volumetric data as a superposition of the voxel values in the axial direction). One way to minimize this problem is by tracking and correcting for retinal motion in real time during acquisition [32

32. R. D. Ferguson, D. X. Hammer, L. A. Paunescu, S. Beaton, and J. S. Schuman, “Tracking optical coherence tomography,” Opt. Lett. 29, 2139–2141 (2004). [CrossRef] [PubMed]

, 33

33. D. W. Arathorn, Q. Yang, C. R. Vogel, Y. Zhang, P. Tiruveedhula, and A. Roorda, “Retinally stabilized conetargeted stimulus delivery,” Opt. Express 15, 13731–13744 (2007). [CrossRef] [PubMed]

] or in post-processing [34

34. C. R. Vogel, D. W. Arathorn, A. Roorda, and A. Parker, “Retinal motion estimation in adaptive optics scanning laser ophthalmoscopy,” Opt. Express 14, 487–497 (2006). [CrossRef] [PubMed]

]. Application of the first method would require construction of a more complex and more costly imaging instrument. The second method requires fast transverse (en-face) image acquisition to track retinal motion that is usually achieved by an SLO, but could also be achieved with future ultrahigh-speed OCT. We do not discuss those issues in detail in this paper. Table 1 compares acquisition times and sampling densities of the two volume acquisition schemes that were tested in this paper.

Table 1. Comparison of Volume Acquisition Times and Lateral Sampling for Two Grids

table-icon
View This Table

2.2.1. Acquisition of large FOV using sub-volumes.

Fig. 1. An example of AO-OCT scanning areas used for creating larger FOV volume (based on the acquisition of nine sub-volumes). Numbers on the sub-volumes refer to the order in which they were acquired. Fundus photo is used for reference.

2.3. Manual stitching and visualization of sub-volumes

To stitch sub-volumes we have incorporated additional functionality into our OCT volume renderer, described previously [36

36. R. J. Zawadzki, A. R. Fuller, D. F. Wiley, B. Hamann, S. S. Choi, and J. S. Werner, “Adaptation of a support vector machine algorithm for segmentation and visualization of retinal structures in volumetric optical coherence tomography data sets,” J. Biomed. Opt. 12, 041206 (2007). [CrossRef] [PubMed]

], to permit independent manipulation of each sub-volume (free translation, one at a time in three dimensions) and viewing of the resulting volume and its cross-sectional slices in real time. This allows for accurate and timely stitching of several sub-volumes within minutes. After proper positioning of sub-volumes data can then be “stitched” and saved as a single large volume. This step is then repeated until a large FOV volume consisting of all sub-volumes is created. The figure below shows a simplified flow chart of our manual sub-volume registration and stitching procedure.

Fig. 2. A simple flow chart representing the process of sub-volume co-registration and stitching.

There are various ways of combining the data in the overlapping regions (usually by 10–15%) of two sub-volumes. We currently choose the maximum value of two overlaying voxels as the value of the resulting voxel in order to preserve the prominent characteristics of each volume. This also enhances artifacts if sub-volumes are not aligned properly and therefore helps to co-register them by minimizing it. The figure below shows a schematic of the manual volume manipulation allowed during sub-volume registration.

Fig. 3. Left, schematic of the volume manipulation allowed during manual volume stitching in our volume renderer. Right, resulting volume with common voxels.

2.3.1. Co-registration of AO-OCT volumetric datasets with other imaging modalities

As already pointed out, due to the growing reliance on Fourier-domain OCT in ophthalmological diagnoses, it is increasingly important to be able to compare results obtained with this instrument to other clinical imaging systems. This task is trivial if the OCT instrument itself is a part of such a system, but no system combines all the relevant clinical images that may be needed for a given subject. Thus, cross-platform registration needs to be implemented. This problem is quite complex as the scaling and distortions between imaging platforms may not be linear. In this work, we implemented simplified co-registration using only scaling, translation and rotation of co-registered images. Similarly to the aforementioned stitching and visualization of sub-volumes, this functionality has been incorporated into our OCT volume renderer [36

36. R. J. Zawadzki, A. R. Fuller, D. F. Wiley, B. Hamann, S. S. Choi, and J. S. Werner, “Adaptation of a support vector machine algorithm for segmentation and visualization of retinal structures in volumetric optical coherence tomography data sets,” J. Biomed. Opt. 12, 041206 (2007). [CrossRef] [PubMed]

] for manipulation and viewing of a co-registered image on the corresponding OCT volume, its OCT fundus image and cross-sectional slices. In our current system we can freely scale, rotate and translate a fundus photo in three dimensions. Our system currently allows this transformation to be manipulated directly or by matching points from the fundus photo to a two-dimensional projection of the OCT dataset (OCT fundus). This point correlation approach operates solely in a two-dimensional domain, thus only two sets of correlated points are needed to completely define this transformation. Such manipulation is accomplished with the co-registered image only (OCT data remains unchanged). This approach allows the segmentations and annotations (any drawings / marks made on OCT cross-sectional planes) imposed on the OCT volume to be displayed on the coregistered fundus photo. Figure 4 shows a schematic of the image manipulation allowed during this registration process.

Fig. 4. Schematic of the manipulation allowed during co-registration of the fundus photo (green rectangle) with the OCT volume.

3. Results and discussion

In this section, several examples of retinal structures acquired with our UHR-AO-OCT system offering high isotropic resolution of 3.5µm are presented.

3.1. UHR-AO-OCT retinal imaging

Fig. 5. UHR-AO-OCT volume of the retinal structures acquired over 0.25×0.3 mm area on the 4.5 deg temporal retina (TR). Top row: left, visualization of the data acquired with UHR-AOOCT system focus set on photoreceptor layers; center, fundus photo with marked location of the acquired volumes; right, visualization of the data acquired with UHR-AO-OCT system focus set on inner retinal layers. Bottom row: left, screenshot from OSA ISP with the UHRAO-OCT volume with focus set on photoreceptor layers (View 1); right, screenshot from OSA ISP with the UHR-AO-OCT volume and focus set on inner retina layers (View 2). Multiple microscopic and cellular structures can be recognized clearly (including photoreceptors seen on the lower left panel and microcapillaries seen on the lower right panel).

UHR-AO-OCT volumetric retinal imaging with large FOV volumes, exceeding our current system FOV of ~ 1mm, similarly to other AO imaging modalities (that also have a small field of view), can be achieved by acquiring multiple volumes and merging them into a “montage.” As an example, Fig. 6 shows a set of nine volumes acquired (as described in paragraph 2.2.1) covering approximately 2.5×2.5 mm area on the retina. The figure shows a screenshot from our custom volume renderer with an OCT fundus view of the final volumetric montage with co-registered fundus photo. Each sub-volume covers 1×1 mm and was acquired using the large volume acquisition mode. Registration of the sub-volumes and subsequent co-registration between the resulting large FOV AO-OCT volume and fundus photo was achieved by manipulating this data through the user friendly interface of our volume rendering software. The large FOV is likely to facilitate clinical and scientific applications of AO-OCT.

Fig. 6. OCT fundus montage created with our volume renderer of nine stitched AO-OCT 1×1 mm sub-volumes acquired with focus set on inner retinal layers.

It can be seen that small retinal vessels can be used as anchor points for co-registration of AO-OCT volumes to fundus photos. As a result of this co-registration one can interactively view with our volume renderer both the AO-OCT volume and fundus photo to achieve better visualization and localization of the retinal features between two imaging modalities. As an example of the volumetric view of a large FOV AO-OCT volume, Fig. 7 shows a screenshot of an image generated with our volume renderer. It can be seen that even though vertical spacing between consecutive B-scans is approximately 10 µm, microscopic retinal features can be recognized easily.

Fig. 7. Visualization of the large FOV AO-OCT volume (from Fig. 5). Left, movie of the volume with co-registered fundus photo generated with our custom visualization software (Media 1). Right, screenshot from OSA ISP with the slicing plane view of the large FOV AOOCT volume (View 3). Note the clear visualization of microcapillaries and foveal avascular zone when altering the location of the slicing plane.

We submit that the creation and display of large FOV AO-OCT volumes greatly improves the potential clinical impact of our AO-OCT system. This functionality will be further enhanced when combined with more automated data acquisition and stitching procedures to be developed in the future.

3.2. AO-OCT ONH imaging

To illustrate the use of AO-OCT for visualization of retinal structures outside the fovea, we imaged the optic nerve head (ONH) of a healthy 50-year-old volunteer. The AO-OCT system used for ONH imaging was an earlier version of the UHR-AO-OCT mentioned above. The two main differences are: reduced axial resolution (6 µm) and fixed wavefront correction during imaging. Both were dictated by current constraints of our UHR-AO-OCT instrument. The reduction of axial resolution was forced by the presence of transverse chromatic aberrations (TCA). This aberration is responsible for lateral blur of the imaging spot and increased with spectral bandwidth and eccentricity of the imaged structure [30

30. R. J. Zawadzki, B. Cense, Y. Zhang, S. S. Choi, D. T. Miller, and J. S. Werner, “Ultrahigh-resolution optical coherence tomography with monochromatic and chromatic aberration correction,” Opt. Express 16, 8126–8143 (2008). [CrossRef] [PubMed]

, 37

37. E. Fernández and W. Drexler, “Influence of ocular chromatic aberration and pupil size on transverse resolution in ophthalmic adaptive optics optical coherence tomography,” Opt. Express 13, 8184–8197 (2005). [CrossRef] [PubMed]

]. Thus, reduction of spectral bandwidth helped to limit the degrading impact of TCA on image quality. Imaging with fixed wavefront correction was forced by our AO-OCT imaging scheme where the same light is used for both imaging and wavefront sensing. Thus, while imaging structures like the ONH, with variation in axial location, no stable reference plane (in depth) can be used by the wavefront sensor, thereby reducing the stability of AO correction. To overcome this problem we closed our AO loop while scanning the imaging beam outside the ONH and then, after fixing the wavefront corrector, asked the subject to look in the direction allowing one to image the region of interest in the ONH.

Fig. 8. Visualization of the ONH microscopic structures imaged with AO-OCT. Left, screenshot from our custom volume renderer after co-registration of five 3D AO-OCT datasets with fundus photo. Right, screenshots from movies showing B-scan and cross-sectional view [26] of three AO-OCT volumes shown on the left: 15N 2SR (Media 2), 12NR (Media 3), and 14N 2IR (Media 4). White lines on the B-scans correspond to the depth of the C-scans reconstructed from the same volume. Multiple microscopic structures including lamina cribosa and blood vessels are easily recognizable. All the volumes can be accessed and viewed with OSA ISP: 12NR (View 4), 14N 2IR (View 5), 15N 2SR (View 6), 17N 1SR (View 7), and 16N 6SR (View 8). Note that the volume acquired at 17N 1SR has motion distortion that could not be properly corrected.

Several features that may be used in the diagnosis of retinal diseases can be visualized and recognized clearly, including the microscopic morphology of the ONH rim and lamina cribosa. Squares superimposed on the fundus photograph of the subject’s ONH are used to denote the locations where high-resolution AO-OCT images were acquired. Single B-scans from full volumes and reconstructed C-scans are also presented.

4. Conclusions

The utility of UHR-AO-OCT volumetric imaging for research and clinical application is still being evaluated. Image understanding seldom follows immediately from hardware development. Instead, new imaging modalities may require not only clinical testing but novel visualization methods, especially with volumetric data providing unfamiliar views to clinicians. We have shown several examples of the application of our UHR-AO-OCT system for imaging volumetric retinal structures at cellular resolution. As can be seen in the two examples, AO-OCT helps to visualize volumetric micro-morphology of retinal structures that should allow monitoring disease progression or treatment on a microscopic scale. It also may provide a unique tool for the study of retinal disease as structures may now be seen that were previously available only through histological methods and necessarily at only one time point in the course of the disease.

Our current UHR-AO-OCT volumes suffer from retinal motion artifacts that cannot be removed due to insufficient acquisition speed. This of course translates into motion artifacts on the stitched sub-volumes making it more difficult to co-register. Additionally, since retinal eccentricity is chosen by changing the location of a fixation point, a nonlinear distortion of the AO-OCT volumes can be observed between sub-volumes. This effect creates additional artifacts on stitched volumes. In this case, more complex sub-volume manipulation (beyond simple translation) would be necessary to limit these artifacts.

Acknowledgements

We gratefully acknowledge the contributions of Steven M. Jones, Diana Chen and Scot S. Olivier from Lawrence Livermore National Laboratory for providing AO support. Help from Joseph A. Izatt from the Department of Biomedical Engineering, Duke University Durham, North Carolina. and Bioptigen Inc., Durham, North Carolina for providing OCT data acquisition software is appreciated. Alfred Fuller was supported by a Student Employee Graduate Research Fellowship (SEGRF) via Lawrence Livermore National Laboratory. Julia W. Evans has been partially supported by funding from the National Science Foundation. The Center for Biophotonics, an NSF Science and Technology Center, is managed by the University of California, Davis, under Cooperative Agreement No. PHY 0120999. This research was supported by the National Eye Institute (grant EY 014743).

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30.

R. J. Zawadzki, B. Cense, Y. Zhang, S. S. Choi, D. T. Miller, and J. S. Werner, “Ultrahigh-resolution optical coherence tomography with monochromatic and chromatic aberration correction,” Opt. Express 16, 8126–8143 (2008). [CrossRef] [PubMed]

31.

E. J. Fernández, B. Hermann, B. Považay, A. Unterhuber, H. Sattmann, B. Hofer, P. K. Ahnelt, and W. Drexler, “Ultrahigh-resolution optical coherence tomography and pancorrection for cellular imaging of the living human retina,” Opt. Express 16, 11083–11094 (2008). [CrossRef] [PubMed]

32.

R. D. Ferguson, D. X. Hammer, L. A. Paunescu, S. Beaton, and J. S. Schuman, “Tracking optical coherence tomography,” Opt. Lett. 29, 2139–2141 (2004). [CrossRef] [PubMed]

33.

D. W. Arathorn, Q. Yang, C. R. Vogel, Y. Zhang, P. Tiruveedhula, and A. Roorda, “Retinally stabilized conetargeted stimulus delivery,” Opt. Express 15, 13731–13744 (2007). [CrossRef] [PubMed]

34.

C. R. Vogel, D. W. Arathorn, A. Roorda, and A. Parker, “Retinal motion estimation in adaptive optics scanning laser ophthalmoscopy,” Opt. Express 14, 487–497 (2006). [CrossRef] [PubMed]

35.

S. S. Choi, R. J. Zawadzki, J. L. Keltner, and J. S. Werner, “Changes in cellular structures revealed by ultrahighresolution retinal imaging in optic neuropathies,” Invest. Ophthalmol. Vis. Sci. 49, 2103–2119 (2008). [CrossRef] [PubMed]

36.

R. J. Zawadzki, A. R. Fuller, D. F. Wiley, B. Hamann, S. S. Choi, and J. S. Werner, “Adaptation of a support vector machine algorithm for segmentation and visualization of retinal structures in volumetric optical coherence tomography data sets,” J. Biomed. Opt. 12, 041206 (2007). [CrossRef] [PubMed]

37.

E. Fernández and W. Drexler, “Influence of ocular chromatic aberration and pupil size on transverse resolution in ophthalmic adaptive optics optical coherence tomography,” Opt. Express 13, 8184–8197 (2005). [CrossRef] [PubMed]

OCIS Codes
(010.1080) Atmospheric and oceanic optics : Active or adaptive optics
(110.4500) Imaging systems : Optical coherence tomography
(120.3890) Instrumentation, measurement, and metrology : Medical optics instrumentation
(170.0110) Medical optics and biotechnology : Imaging systems
(170.4470) Medical optics and biotechnology : Ophthalmology
(220.1000) Optical design and fabrication : Aberration compensation

ToC Category:
OCT Technology

History
Original Manuscript: August 22, 2008
Revised Manuscript: February 11, 2009
Manuscript Accepted: February 11, 2009
Published: March 2, 2009

Virtual Issues
Vol. 4, Iss. 5 Virtual Journal for Biomedical Optics
Interactive Science Publishing Focus Issue: Optical Coherence Tomography (OCT) (2009) Optics Express

Citation
Robert J. Zawadzki, Stacey S. Choi, Alfred R. Fuller, Julia W. Evans, Bernd Hamann, and John S. Werner, "Cellular resolution volumetric in vivo retinal imaging with adaptive optics–optical coherence tomography," Opt. Express 17, 4084-4094 (2009)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=oe-17-5-4084


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