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Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 18, Iss. 13 — Jun. 21, 2010
  • pp: 13935–13944
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In vivo investigation of human cone photoreceptors with SLO/OCT in combination with 3D motion correction on a cellular level

Michael Pircher, Erich Götzinger, Harald Sattmann, Rainer A. Leitgeb, and Christoph K. Hitzenberger  »View Author Affiliations


Optics Express, Vol. 18, Issue 13, pp. 13935-13944 (2010)
http://dx.doi.org/10.1364/OE.18.013935


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Abstract

We present a further improvement of our SLO/OCT imaging system which enables to practically eliminate all eye motion artifacts with a correction accuracy approaching sub-cellular dimensions. Axial eye tracking is achieved by using a hardware based, high speed tracking system that consists of a rapid scanning optical delay line in the reference arm of the interferometer. A software based algorithm is employed to correct for transverse eye motion in a post-processing step. The instrument operates at a frame rate of 40 en-face fps with a field of view of ~1°x1°. Dynamic focusing enables the recording of 3D volumes of the human retina with cellular resolution throughout the entire imaging depth. Several volumes are stitched together to increase the total field of view. Different features of the three dimensional structure of cone photoreceptors are investigated in detail and at different eccentricities from the fovea.

© 2010 OSA

1. Introduction

In the recent years optical coherence tomography (OCT) has evolved into an important retinal imaging technique [1

1. M. E. J. van Velthoven, D. J. Faber, F. D. Verbraak, T. G. van Leeuwen, and M. D. de Smet, “Recent developments in optical coherence tomography for imaging the retina,” Prog. Retin. Eye Res. 26(1), 57–77 (2007). [CrossRef]

3

3. A. G. Podoleanu and R. B. Rosen, “Combinations of techniques in imaging the retina with high resolution,” Prog. Retin. Eye Res. 27(4), 464–499 (2008). [CrossRef] [PubMed]

]. Many papers have been published so far that demonstrated the clinical value of this technique [4

4. U. Schmidt-Erfurth, R. A. Leitgeb, S. Michels, B. Povazay, S. Sacu, B. Hermann, C. Ahlers, H. Sattmann, C. Scholda, A. F. Fercher, and W. Drexler, “Three-dimensional ultrahigh-resolution optical coherence tomography of macular diseases,” Invest. Ophthalmol. Vis. Sci. 46(9), 3393–3402 (2005). [CrossRef] [PubMed]

7

7. V. J. Srinivasan, M. Wojtkowski, A. J. Witkin, J. S. Duker, T. H. Ko, M. Carvalho, J. S. Schuman, A. Kowalczyk, and J. G. Fujimoto, “High-definition and 3-dimensional imaging of macular pathologies with high-speed ultrahigh-resolution optical coherence tomography,” Ophthalmology 113(11), 2054–2065.e3 (2006). [CrossRef] [PubMed]

]. However, imaging the retina on a cellular level is still challenging because of two reasons. First, imperfections of the optics of the eye will introduce aberrations to the imaging beam and will therefore degrade the resolution of retinal images in the majority of subjects. It has been shown that with the implementation of adaptive optics (AO) these aberrations can be compensated in many subjects, yielding a nearly diffraction limited image resolution [8

8. A. Roorda and D. R. Williams, “The arrangement of the three cone classes in the living human eye,” Nature 397(6719), 520–522 (1999). [CrossRef] [PubMed]

12

12. 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]

]. Second, at the high magnification needed to resolve individual cells, subject and/or eye motion is very pronounced and can therefore be a severe problem. While scanning laser ophthalmoscope (SLO) and flood illumination systems are capable to record two dimensional images rapidly to minimize these artifacts, the 3D imaging speed of conventional OCT systems is rather limited (even with the use of high speed cameras that provide scan rates of ~200000 A-scans per second) [13

13. B. Potsaid, I. Gorczynska, V. J. Srinivasan, Y. L. Chen, J. Jiang, A. Cable, and J. G. Fujimoto, “Ultrahigh speed spectral / Fourier domain OCT ophthalmic imaging at 70,000 to 312,500 axial scans per second,” Opt. Express 16(19), 15149–15169 (2008). [CrossRef] [PubMed]

15

15. T. Schmoll, C. Kolbitsch, and R. A. Leitgeb, “Ultra-high-speed volumetric tomography of human retinal blood flow,” Opt. Express 17(5), 4166–4176 (2009). [CrossRef] [PubMed]

].

To overcome the problem with aberrations introduced by imperfect eye optics we investigated in this study only retinal images of healthy volunteers with good eye optics. Several groups have demonstrated that in these special cases individual cone photoreceptors can be resolved within OCT images in vivo without the use of AO [13

13. B. Potsaid, I. Gorczynska, V. J. Srinivasan, Y. L. Chen, J. Jiang, A. Cable, and J. G. Fujimoto, “Ultrahigh speed spectral / Fourier domain OCT ophthalmic imaging at 70,000 to 312,500 axial scans per second,” Opt. Express 16(19), 15149–15169 (2008). [CrossRef] [PubMed]

, 15

15. T. Schmoll, C. Kolbitsch, and R. A. Leitgeb, “Ultra-high-speed volumetric tomography of human retinal blood flow,” Opt. Express 17(5), 4166–4176 (2009). [CrossRef] [PubMed]

17

17. M. Pircher, B. Baumann, E. Götzinger, H. Sattmann, and C. K. Hitzenberger, “Simultaneous SLO/OCT imaging of the human retina with axial eye motion correction,” Opt. Express 15(25), 16922–16932 (2007). [CrossRef] [PubMed]

]. Furthermore we address the problem of eye motion artifacts by minimizing them using a high speed transverse scanning OCT/SLO (TS-OCT/SLO) system that incorporates a fast axial eye motion correction device and a software based transverse eye motion correction algorithm.

In this paper we report on improvements of our instrument in terms of minimizing eye motion artifacts (axial and transverse). This motion correction approaches, what we believe for the first time, sub-cellular accuracy. The improved instrument enables to record several adjacent patches of the retina with cellular resolution throughout imaging depth and stitching of 3D data sets to generate large field of view images with cellular resolution. Finally we measure the cone density at different eccentricities from the fovea for several subjects, identify new features within the cone outer segments and present, what we believe for the first time, measurements of the density of these features.

2. Method

In order to improve the signal intensity in the SLO channel we slightly changed the configuration of the main interferometer in the following way. The incident light is linear polarized by a polarizer. The light traverses a polarizing beam splitter and is split into sample and reference beam. By rotation of the polarizer the splitting ratio of the light at the polarizing beam splitter can be adjusted in order to achieve 700µW incident on the cornea. In the sample arm the light traverses an additional polarizing beam splitter, a non polarizing beam splitter and is directed via telescope optics to the scanners and finally to the eye. In this configuration the pivot points of both scanners are imaged into the pupil plane of the eye. The second lens (L2 in Fig. 1) is mounted on a translation stage which enables the adjustment of the focus and dynamic focusing during the 3D measurements [18

18. M. Pircher, E. Gotzinger, and C. K. Hitzenberger, “Dynamic focus in optical coherence tomography for retinal imaging,” J. Biomed. Opt. 11(5), 054013 (2006). [CrossRef] [PubMed]

]. A quarter wave plate oriented at 45 degrees with respect to the incident polarization state is placed after the final lens in the sample arm (L4 in Fig. 1) which resembles together with the second PBS a bulk optics circulator. This ensures that 50 percent of the light returning from the retina is directed to the SLO detector (assuming negligible birefringence of the sample). The rest of the light is collected by the OCT detectors. A pellicle beam splitter (more than 90% of the light is transmitted) is placed between the lenses L3 and L4 which allows the measured subject to fixate on variable patterns on the fixation target (FT). The FT itself consists of an organic light emitting diode (OLED) display. Note that the measured eye is used for fixation which is essential to minimize transverse eye motion.

In the reference arm the light beam traverses two acousto optic modulators in order to generate a net frequency shift of 1MHz (carrier frequency) and is directed via a polarizing beam splitter and a quarter wave plate (equivalent to a bulk optics circulator) to the RSOD. The light returning from the RSOD is directed to a translation stage for depth scanning and a half wave plate in order to rotate the polarization plane by 90 degrees to match the polarization plane returning from the sample arm. Reference light and sample light are combined at the final beam splitter of the interferometer. Both interferometer exits are used which provides balanced detection. Currently the imaging speed is 40 frames (650 (x) x 200 (y) pixels) per second, covering an area of ~300 x 300µm2 on the retina. The axial resolution of the OCT is given by the bandwidth of the used light source (λ0 = 840nm, ∆λ = 50nm) and is estimated with ~5µm in retinal tissue (assuming a refractive index of 1.4 within the retina). The diffraction limited lateral resolution of the system was estimated with 5µm.

3. Imaging protocol and post processing

This averaged frame was used in a second alignment step as new reference frame to minimize any influences (e.g. slight distortions) of the first reference frame. The obtained translation matrix of this procedure was used to correct the OCT images (They have a pixel to pixel correspondence with the SLO images). Together with the axial eye tracking this transverse motion correction algorithm resulted in nearly motion artifact free 3D volumes of the retina. Moreover, because of the unique pattern of the cone mosaic 3D volumes recorded at different times could be aligned to each other with an accuracy that is better than the lateral extension of a single cone. This feature was used to further minimize errors (e.g. differing light coupling ratio into cone photoreceptors, residual depth tracking error) by recording for each eccentricity 5 data sets that were aligned to each other and averaged. Data was recorded at 8 different eccentricities from the fovea.

4. Results

To demonstrate the performance of the system in terms of axial eye motion correction we recorded eight adjacent 3D data sets of the entire retinal depth with increasing eccentricities from the fovea (step size 0.5°). The eight data sets have been stitched together to cover an area of ~5°x1°. Figure 2
Fig. 2 (Media 1) Frame number 65 of a movie retrieved from a 3D data set recorded with the instrument. The movie starts from the anterior part of the retina to the posterior part. Field of view: ~5°x1°. Imaging depth: ~393µm (in tissue). Images are represented in a logarithmic intensity scale.
shows a “fly through” movie from the anterior part of the retina to the posterior part and Fig. 3
Fig. 3 (Media 2) Frame number 50 of a movie retrieved from the same data set as in Fig. 2. The movie starts from the inferior part of the retina to the superior part. Image size: 5° x 393µm (in tissue) Images are represented in a logarithmic intensity scale.
the corresponding B-scan “fly through” movie of the same data set. Note that the dynamic focus ensures that the entire depth of the retina is in focus. As the first movie starts, individual nerve fiber bundles within the nerve fiber layer can be observed. As the coherence plane is moved further into tissue, small capillaries in the ganglion cell layer as well as at the top and bottom of the inner nuclear layer can be seen. Deeper into the tissue the external limiting membrane (faint signal) is followed by the junction between inner and outer segments of photoreceptors and the end tips of photoreceptors. Both layers show the cone mosaic. The last layer visible in the movie is the retinal pigment epithelium. The B-scan movie shows the excellent performance of the system to correct for axial eye motion correction.

Note that due to the large field of view shown in the movie (with limited memory size) the resolution of the original data was reduced and without zooming into the original data set individual cone photoreceptors are rather hardly visible. A slight mismatch in axial direction can be observed between individual 3D data sets. This mismatch varies in y-direction and is caused by a slightly changing entrance pupil (vertical position) of the imaging beam from data set to data set. This mismatch might be compensated using an A-scan based correction algorithm on the final data set.

However, the measured density of the BRs follows a different dependence on the eccentricity from the fovea (c.f. Figure 7b). In four volunteers we observed an increase of BR with eccentricity with a maximum of BR density at ~4° eccentricity. At larger eccentricities this density decreases again. One volunteer showed almost constant BR density with eccentricity. We want to emphasize here that even though we are not able to resolve individual cones at eccentricities smaller than 2° it is still possible to count the BR’s at these eccentricities provided that these are quite isolated (which is the case at larger eccentricities).

Although we counted every BR for the measurement above we observed differing arrangements of these spots with respect to the normal reflections from the IS/OS junction and ETPR layer. Figure 9
Fig. 9 Different arrangements of BR (marked with an ellipse) observed at 4° eccentricity (see text for explanation).
illustrates five different possibillities: a) Three distinct spots can be observed but the spot from within the outer segment has the highest intensity, b) Three distinct spots with equal intensity, c) only one highly reflecting spot, d) one spot within the outer segments, one within the ETPR layer, e) one spot within the IS/OS junction and one within the outer segments (no reflection from the ETPR).

5. Discussion and conclusion

We introduced an improved version of our transverse scanning OCT/SLO system. With this technique nearly motion artifact free 3D volumes of the retina with cellular resolution throughout the entire imaging depth could be obtained. We showed the possibility to stitch several 3D data stacks together in order to enlarge the total field of view. With the new system we could overcome a limitation of all other currently used OCT techniques that suffer from both: transverse eye motion artifacts and limited depth of focus.

This allowed us to investigate the human cone mosaic of five volunteers in more detail. The measured cone density at different eccentricities from the fovea was found in excellent agreement with data known from histology and represents the first study of this kind using OCT without the use of adaptive optics. We want to emphasize here that a similar study was performed more than a decade ago with a SLO [30

30. D. T. Miller, D. R. Williams, G. M. Morris, and J. Liang, “Images of cone photoreceptors in the living human eye,” Vision Res. 36(8), 1067–1079 (1996). [CrossRef] [PubMed]

, 31

31. A. R. Wade and F. W. Fitzke, “In-vivo imaging of the human cone photoreceptor mosaic using a confocal LSO,” Lasers and Light in Ophthalmology 8, 129–136 (1998).

]. However, in contrast to AO equipped systems the cone mosaic could only be observed down to two degrees eccentricity from the fovea because of the limited resolution of the system. Additionally we introduced, to the best of our knowledge for the first time, measurements of the density of bright reflections that can be observed in OCT images within the outer segments of cone photoreceptors. To minimize influences of differing light coupling efficiencies into the cone photoreceptors five 3D data sets were recorded and averaged. The BRs were categorized into five different appearances. Due to the different appearances of the BRs we can conclude that these BRs are not caused by multiple reflection between IS/OS and ETPR. (These should have a longer path and should appear at the level of the RPE or below). Although the origin of these bright reflections is, at this stage of investigation still unclear, one might speculate about their histological counterparts. Interestingly, a similar distribution as shown in Fig. 7b) can be found in histology for blue or S-cones [32

32. F. M. de Monasterio, E. P. McCrane, J. K. Newlander, and S. J. Schein, “Density Profile of Blue-Sensitive Cones Along the Horizontal Meridian of Macaque Retina,” Invest. Ophthalmol. Vis. Sci. 26(3), 289–302 (1985). [PubMed]

]. These cones are also known to be shorter than the other (L and M) cones; however the difference should be in the order of only a few percent. Moreover, S-cones should have the maximum density closer to the fovea at ~1-2 degrees eccentricity. Therefore, the correlation with the S-cone distribution might be accidental. Another possibility might be that the BRs represent cone outer segments that underwent phagocytosis. In this case the depth position of the BRs should change over time. However, in a preliminary study we observed that the BRs density did not change within 48 hours [19

19. M. Pircher, B. Baumann, H. Sattman, E. Gotzinger, and C. K. Hitzenberger, “High speed, high resolution SLO/OCT for investigating temporal changes of single cone photoreceptors in vivo,” Proc. SPIE 7372, 13 (2009).

].

Acknowledgement

Financial support from the Austrian Science Fund (FWF grant P19624-B02) is acknowledged.

References and links

1.

M. E. J. van Velthoven, D. J. Faber, F. D. Verbraak, T. G. van Leeuwen, and M. D. de Smet, “Recent developments in optical coherence tomography for imaging the retina,” Prog. Retin. Eye Res. 26(1), 57–77 (2007). [CrossRef]

2.

W. Drexler and J. G. Fujimoto, “State-of-the-art retinal optical coherence tomography,” Prog. Retin. Eye Res. 27(1), 45–88 (2008). [CrossRef]

3.

A. G. Podoleanu and R. B. Rosen, “Combinations of techniques in imaging the retina with high resolution,” Prog. Retin. Eye Res. 27(4), 464–499 (2008). [CrossRef] [PubMed]

4.

U. Schmidt-Erfurth, R. A. Leitgeb, S. Michels, B. Povazay, S. Sacu, B. Hermann, C. Ahlers, H. Sattmann, C. Scholda, A. F. Fercher, and W. Drexler, “Three-dimensional ultrahigh-resolution optical coherence tomography of macular diseases,” Invest. Ophthalmol. Vis. Sci. 46(9), 3393–3402 (2005). [CrossRef] [PubMed]

5.

T. C. Chen, B. Cense, M. C. Pierce, N. Nassif, B. H. Park, S. H. Yun, B. R. White, B. E. Bouma, G. J. Tearney, and J. F. de Boer, “Spectral domain optical coherence tomography: Ultra-high speed, ultra-high resolution ophthalmic imaging,” Arch. Ophthalmol. 123(12), 1715–1720 (2005). [CrossRef] [PubMed]

6.

S. Alam, R. J. Zawadzki, S. Choi, C. Gerth, S. S. Park, L. Morse, and J. S. Werner, “Clinical application of rapid serial fourier-domain optical coherence tomography for macular imaging,” Ophthalmology 113(8), 1425–1431 (2006). [CrossRef] [PubMed]

7.

V. J. Srinivasan, M. Wojtkowski, A. J. Witkin, J. S. Duker, T. H. Ko, M. Carvalho, J. S. Schuman, A. Kowalczyk, and J. G. Fujimoto, “High-definition and 3-dimensional imaging of macular pathologies with high-speed ultrahigh-resolution optical coherence tomography,” Ophthalmology 113(11), 2054–2065.e3 (2006). [CrossRef] [PubMed]

8.

A. Roorda and D. R. Williams, “The arrangement of the three cone classes in the living human eye,” Nature 397(6719), 520–522 (1999). [CrossRef] [PubMed]

9.

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(11), 2884–2892 (1997). [CrossRef]

10.

M. Pircher and R. Zawadzki, “Combining adaptive optics with optical coherence tomography: Unveiling the cellular structure of the human retina in vivo,” Expert Rev. Ophthalmol. 2(6), 1019 (2007). [CrossRef]

11.

J. Liang, D. R. Williams, and D. T. Miller, “High resolution imaging of the living human retina with adaptive optics,” Invest. Ophthalmol. Vis. Sci. 38, 55–55 (1997).

12.

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]

13.

B. Potsaid, I. Gorczynska, V. J. Srinivasan, Y. L. Chen, J. Jiang, A. Cable, and J. G. Fujimoto, “Ultrahigh speed spectral / Fourier domain OCT ophthalmic imaging at 70,000 to 312,500 axial scans per second,” Opt. Express 16(19), 15149–15169 (2008). [CrossRef] [PubMed]

14.

C. Torti, B. Povazay, B. Hofer, A. Unterhuber, J. Carroll, P. K. Ahnelt, and W. Drexler, “Adaptive optics optical coherence tomography at 120,000 depth scans/s for non-invasive cellular phenotyping of the living human retina,” Opt. Express 17(22), 19382–19400 (2009). [CrossRef] [PubMed]

15.

T. Schmoll, C. Kolbitsch, and R. A. Leitgeb, “Ultra-high-speed volumetric tomography of human retinal blood flow,” Opt. Express 17(5), 4166–4176 (2009). [CrossRef] [PubMed]

16.

M. Pircher, B. Baumann, E. Götzinger, and C. K. Hitzenberger, “Retinal cone mosaic imaged with transverse scanning optical coherence tomography,” Opt. Lett. 31(12), 1821–1823 (2006). [CrossRef] [PubMed]

17.

M. Pircher, B. Baumann, E. Götzinger, H. Sattmann, and C. K. Hitzenberger, “Simultaneous SLO/OCT imaging of the human retina with axial eye motion correction,” Opt. Express 15(25), 16922–16932 (2007). [CrossRef] [PubMed]

18.

M. Pircher, E. Gotzinger, and C. K. Hitzenberger, “Dynamic focus in optical coherence tomography for retinal imaging,” J. Biomed. Opt. 11(5), 054013 (2006). [CrossRef] [PubMed]

19.

M. Pircher, B. Baumann, H. Sattman, E. Gotzinger, and C. K. Hitzenberger, “High speed, high resolution SLO/OCT for investigating temporal changes of single cone photoreceptors in vivo,” Proc. SPIE 7372, 13 (2009).

20.

C. K. Hitzenberger, “Measurement of Corneal Thickness by Low-Coherence Interferometry,” Appl. Opt. 31(31), 6637–6642 (1992). [CrossRef] [PubMed]

21.

G. J. Tearney, B. E. Bouma, and J. G. Fujimoto, “High-speed phase- and group-delay scanning with a grating-based phase control delay line,” Opt. Lett. 22(23), 1811–1813 (1997). [CrossRef]

22.

W. Drexler, O. Findl, L. Schmetterer, C. K. Hitzenberger, and A. F. Fercher, “Eye elongation during accommodation in humans: Differences between emmetropes and myopes,” Invest. Ophthalmol. Vis. Sci. 39(11), 2140–2147 (1998). [PubMed]

23.

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(11), 8126–8143 (2008). [CrossRef] [PubMed]

24.

B. Cense, E. Koperda, J. M. Brown, O. P. Kocaoglu, W. H. Gao, R. S. Jonnal, and D. T. Miller, “Volumetric retinal imaging with ultrahigh-resolution spectral-domain optical coherence tomography and adaptive optics using two broadband light sources,” Opt. Express 17(5), 4095–4111 (2009). [CrossRef] [PubMed]

25.

J. I. Yellott Jr., “Spectral Analysis of Spatial Sampling by Photoreceptors: Topological Disorder Prevents Aliasing,” Vision Res. 22(9), 1205–1210 (1982). [CrossRef] [PubMed]

26.

N. J. Coletta and D. R. Williams, “Psychophysical Estimate of Extrafoveal Cone Spacing,” Journal. of the Optical Society of America. a-Optics Image,” Science and Vision. 4, 1503–1513 (1987).

27.

M. Pircher, R. J. Zawadzki, J. W. Evans, J. S. Werner, and C. K. Hitzenberger, “Simultaneous imaging of human cone mosaic with adaptive optics enhanced scanning laser ophthalmoscopy and high-speed transversal scanning optical coherence tomography,” Opt. Lett. 33(1), 22–24 (2008). [CrossRef]

28.

C. A. Curcio, K. R. Sloan, R. E. Kalina, and A. E. Hendrickson, “Human photoreceptor topography,” J. Comp. Neurol. 292(4), 497–523 (1990). [CrossRef] [PubMed]

29.

Y. Zhang, B. Cense, J. Rha, R. S. Jonnal, W. Gao, R. J. Zawadzki, J. S. Werner, S. Jones, S. Olivier, and D. T. Miller, “High-speed volumetric imaging of cone photoreceptors with adaptive optics spectral-domain optical coherence tomography,” Opt. Express 14(10), 4380–4394 (2006). [CrossRef] [PubMed]

30.

D. T. Miller, D. R. Williams, G. M. Morris, and J. Liang, “Images of cone photoreceptors in the living human eye,” Vision Res. 36(8), 1067–1079 (1996). [CrossRef] [PubMed]

31.

A. R. Wade and F. W. Fitzke, “In-vivo imaging of the human cone photoreceptor mosaic using a confocal LSO,” Lasers and Light in Ophthalmology 8, 129–136 (1998).

32.

F. M. de Monasterio, E. P. McCrane, J. K. Newlander, and S. J. Schein, “Density Profile of Blue-Sensitive Cones Along the Horizontal Meridian of Macaque Retina,” Invest. Ophthalmol. Vis. Sci. 26(3), 289–302 (1985). [PubMed]

OCIS Codes
(110.6880) Imaging systems : Three-dimensional image acquisition
(170.4460) Medical optics and biotechnology : Ophthalmic optics and devices
(170.4500) Medical optics and biotechnology : Optical coherence tomography
(330.5310) Vision, color, and visual optics : Vision - photoreceptors

ToC Category:
Medical Optics and Biotechnology

History
Original Manuscript: April 7, 2010
Revised Manuscript: May 25, 2010
Manuscript Accepted: May 25, 2010
Published: June 14, 2010

Virtual Issues
Vol. 5, Iss. 11 Virtual Journal for Biomedical Optics

Citation
Michael Pircher, Erich Götzinger, Harald Sattmann, Rainer A. Leitgeb, and Christoph K. Hitzenberger, "In vivo investigation of human cone photoreceptors with SLO/OCT in combination with 3D motion correction on a cellular level," Opt. Express 18, 13935-13944 (2010)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-18-13-13935


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References

  1. M. E. J. van Velthoven, D. J. Faber, F. D. Verbraak, T. G. van Leeuwen, and M. D. de Smet, “Recent developments in optical coherence tomography for imaging the retina,” Prog. Retin. Eye Res. 26(1), 57–77 (2007). [CrossRef]
  2. W. Drexler and J. G. Fujimoto, “State-of-the-art retinal optical coherence tomography,” Prog. Retin. Eye Res. 27(1), 45–88 (2008). [CrossRef]
  3. A. G. Podoleanu and R. B. Rosen, “Combinations of techniques in imaging the retina with high resolution,” Prog. Retin. Eye Res. 27(4), 464–499 (2008). [CrossRef] [PubMed]
  4. U. Schmidt-Erfurth, R. A. Leitgeb, S. Michels, B. Povazay, S. Sacu, B. Hermann, C. Ahlers, H. Sattmann, C. Scholda, A. F. Fercher, and W. Drexler, “Three-dimensional ultrahigh-resolution optical coherence tomography of macular diseases,” Invest. Ophthalmol. Vis. Sci. 46(9), 3393–3402 (2005). [CrossRef] [PubMed]
  5. T. C. Chen, B. Cense, M. C. Pierce, N. Nassif, B. H. Park, S. H. Yun, B. R. White, B. E. Bouma, G. J. Tearney, and J. F. de Boer, “Spectral domain optical coherence tomography: Ultra-high speed, ultra-high resolution ophthalmic imaging,” Arch. Ophthalmol. 123(12), 1715–1720 (2005). [CrossRef] [PubMed]
  6. S. Alam, R. J. Zawadzki, S. Choi, C. Gerth, S. S. Park, L. Morse, and J. S. Werner, “Clinical application of rapid serial fourier-domain optical coherence tomography for macular imaging,” Ophthalmology 113(8), 1425–1431 (2006). [CrossRef] [PubMed]
  7. V. J. Srinivasan, M. Wojtkowski, A. J. Witkin, J. S. Duker, T. H. Ko, M. Carvalho, J. S. Schuman, A. Kowalczyk, and J. G. Fujimoto, “High-definition and 3-dimensional imaging of macular pathologies with high-speed ultrahigh-resolution optical coherence tomography,” Ophthalmology 113(11), 2054–2065.e3 (2006). [CrossRef] [PubMed]
  8. A. Roorda and D. R. Williams, “The arrangement of the three cone classes in the living human eye,” Nature 397(6719), 520–522 (1999). [CrossRef] [PubMed]
  9. 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(11), 2884–2892 (1997). [CrossRef]
  10. M. Pircher and R. Zawadzki, “Combining adaptive optics with optical coherence tomography: Unveiling the cellular structure of the human retina in vivo,” Expert Rev. Ophthalmol. 2(6), 1019 (2007). [CrossRef]
  11. J. Liang, D. R. Williams, and D. T. Miller, “High resolution imaging of the living human retina with adaptive optics,” Invest. Ophthalmol. Vis. Sci. 38, 55–55 (1997).
  12. 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]
  13. B. Potsaid, I. Gorczynska, V. J. Srinivasan, Y. L. Chen, J. Jiang, A. Cable, and J. G. Fujimoto, “Ultrahigh speed spectral / Fourier domain OCT ophthalmic imaging at 70,000 to 312,500 axial scans per second,” Opt. Express 16(19), 15149–15169 (2008). [CrossRef] [PubMed]
  14. C. Torti, B. Povazay, B. Hofer, A. Unterhuber, J. Carroll, P. K. Ahnelt, and W. Drexler, “Adaptive optics optical coherence tomography at 120,000 depth scans/s for non-invasive cellular phenotyping of the living human retina,” Opt. Express 17(22), 19382–19400 (2009). [CrossRef] [PubMed]
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