OSA's Digital Library

Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editor: Gregory W. Faris
  • Vol. 1, Iss. 6 — Jun. 13, 2006
« Show journal navigation

Adaptive optics flood-illumination camera for high speed retinal imaging

Jungtae Rha, Ravi S. Jonnal, Karen E. Thorn, Junle Qu, Yan Zhang, and Donald T. Miller  »View Author Affiliations


Optics Express, Vol. 14, Issue 10, pp. 4552-4569 (2006)
http://dx.doi.org/10.1364/OE.14.004552


View Full Text Article

Acrobat PDF (1060 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

Current adaptive optics flood-illumination retina cameras operate at low frame rates, acquiring retinal images below seven Hz, which restricts their research and clinical utility. Here we investigate a novel bench top flood-illumination camera that achieves significantly higher frame rates using strobing fiber-coupled superluminescent and laser diodes in conjunction with a scientific-grade CCD. Source strength was sufficient to obviate frame averaging, even for exposures as short as 1/3 msec. Continuous frame rates of 10, 30, and 60 Hz were achieved for imaging 1.8, 0.8, and 0.4 deg retinal patches, respectively. Short-burst imaging up to 500 Hz was also achieved by temporarily storing sequences of images on the CCD. High frame rates, short exposure durations (1 msec), and correction of the most significant aberrations of the eye were found necessary for individuating retinal blood cells and directly measuring cellular flow in capillaries. Cone videos of dark adapted eyes showed a surprisingly rapid fluctuation (~1 Hz) in the reflectance of single cones. As further demonstration of the value of the camera, we evaluated the tradeoff between exposure duration and image blur associated with retina motion.

© 2006 Optical Society of America

1. Introduction

The optical resolution of retina cameras is significantly increased by correcting the eye’s wave aberrations across a large pupil, using for example adaptive optics (AO) [1

1. R. K. Tyson, Principles of Adaptive Optics (Academic Press, New York, 1998).

]. This increase permits the observation of retinal structures at the cellular level, which could not otherwise be seen in the living eye. AO has been successfully applied to a variety of retina camera modalities including the conventional fundus (flood illumination) camera [2

2. 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]

8

8. P. Fournier, G. R. G. Erry, L. J. Otten, A. Larichev, and N. Irochnikov, “Next generation high resolution adaptive optics fundus imager,” in 5th International Workshop on Adaptive Optics for Industry and Medicine, edited by Wenhan Jiang, Proceedings of SPIE Vol. 6018 (SPIE, Bellingham, WA, 2005).

], confocal scanning laser ophthalmoscope (cSLO) [9

9. A. W. Dreher, J. F. Bille, and R. N. Weinreb, “Active optical depth resolution improvement of the laser tomographic scanner,” Appl. Opt. 28, 804–808 (1989). [CrossRef] [PubMed]

,10

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

] and optical coherence tomography (OCT) [11

11. D. T. Miller, J. Qu, R. S. Jonnal, and K. Thorn, “Coherence gating and adaptive optics in the eye,” in Coherence Domain Optical Methods and Optical Coherence Tomography in Biomedicine VII, V. V. Tuchin, J. A. Izatt, and J. G. Fujimoto, eds., Proc. SPIE4956, 65–72 (2003). [CrossRef]

15

15. E. J. Fernández, B. Považay, B. Hermann, A. Unterhuber, H. Sattmann, P. M. Prieto, R. Leitgeb, P. Ahnelt, P. Artal, and W. Drexler W, “Three-dimensional adaptive optics ultrahigh-resolution optical coherence tomography using a liquid crystal spatial light modulator,” Vision Res. 45, 3432–3444 (2005). [CrossRef] [PubMed]

]. The latter two (cSLO and OCT) are typically realized by raster scanning a focused point source across the retina. Scanning readily lends these cameras to high frame rates, e.g., video rate imaging. Conventional fundus imaging, on the other hand, consists of flood-illuminating a patch of retina and then recording, with a 2D detector, the reflected light that exits the eye. While flood illumination is the most common platform for AO retinal imaging, it has not achieved the imaging rates routinely used with AO-SLO and AO-OCT instruments. This is partially because lower rates have been sufficient for many of the experiments intended for these cameras. Higher rates, however, would certainly benefit applications that require quick and extensive surveying of the retina landscape, and temporally resolving fast retinal dynamics (such as blood flow). In general higher rates should improve effectiveness of the AO flood illumination modality as a research and clinical tool. Another desirable camera feature is flexible control of the exposure duration. Current AO flood-illumination cameras are often hardwired to a fixed value or exceedingly long (up to 100 msec). The former prevents the use of optimal exposure durations for specific experiments, and the latter may expose the retinal image to unacceptable retina motion blur [16

16. L. A. Riggs, J. C. Armington, and J.C., “Motions of the retinal image during fixation,” J. Opt. Soc. Am. 44, 315–321 (1954). [CrossRef] [PubMed]

]. Interestingly, some high resolution flood-illumination cameras have reported even longer exposures, e.g. 300 msec [17

17. I. Iglesias and P. Artal, “High-resolution retinal images obtained by deconvolution from wave-front sensing,” Opt. Lett. 25, 1804–1806 (2000). [CrossRef]

].

The camera components that largely limit frame rate and exposure duration are the illumination light source and 2D detector array (CCD) that captures the retinal image. General light source requirements include low spatial coherence (reduces speckle noise), a narrow spectral band (avoids ocular chromatic aberrations), uniform illumination, and high optical energy deliverable during a short exposure (overcomes the ~10-4 loss in the eye and retina motion blur). In addition, the Lagrange invariant fundamentally limits the efficiency of the illumination channel as dictated by the size and divergence of the light source, the numerical aperture of the eye, and the desired illumination patch (field of view). To meet these requirements, AO flood illumination cameras have employed Krypton and Xenon flash lamps or Mercury and Xenon arc lamps to illuminate the retina. For detection, they have relied on CCD cameras of high sensitivity, but with relatively slow readout rates.

As an alternative, we investigate here a novel bench top AO flood-illumination camera that incorporates, for illuminating the retina, superluminescent and laser diodes cascaded with lengths of multimode optical fiber. Both sources are evaluated separately and used in conjunction with a high-speed scientific-grade CCD. In addition to faster modulation (higher frame rates), higher efficiency (shorter exposure durations) and greater software control, the fiber-coupled light sources are less expensive and more compact than flash and arc lamps. One distinct disadvantage is that SLDs and laser diodes are commercially available at only specific wavelengths. This is unlike arc and flash lamps that radiate broadly over the visible and near-infrared spectrum, and are tunable with choice of an appropriate interference filter.

We demonstrate the utility of our camera by imaging the in vivo retina at various locations and at various frame rates up to 60 Hz (continuous) and 500 Hz (short burst). Additionally, we demonstrate the flexibility of the camera to image over a broad range of exposure durations (1/3 to 100 msec) by using this feature to directly assess the impact of retina motion blur on cone image quality. Accounts of this work were presented at the 2003 and 2005 ARVO, 2004 OSA, and 2004 SPIE meetings [18

18. K. E. Thorn, J. Qu, R. J. Jonnal, and D. T. Miller, “Adaptive optics flood-illuminated camera for high speed retinal imaging,” Invest. Ophthalmol. Visual Sci. 44, E-Abstract 1002 (2003).

21

21. J. Rha, R. S. Jonnal, Y. Zhang, and D. T. Miller, “Video rate imaging with a conventional flood illuminated adaptive optics retin,a camera,” 88th Optical Society of America Annual Meeting, Rochester, New York, October 10–14, 2004.

]. We previously employed a near-infrared prototype version of the fiber-coupled superluminescent diode (SLD) to evaluate an AO-OCT camera [13

13. Y. Zhang, J. Rha, R. Jonnal, and D. Miller, “Adaptive optics parallel spectral domain optical coherence tomography for imaging the living retina,” Opt. Express 13, 4792–4811 (2005). [CrossRef] [PubMed]

].

2. Methods

2.1 Adaptive optics retina camera

A flood-illumination retina camera was developed for collecting aerial images of microscopic structures in the living human retina. The camera consisted of three sub-systems: (1) adaptive optics for compensation of the eye’s wave aberrations, (2) pupil retro-illumination and fixation channel for alignment of the subject’s eye to the camera, and (3) retinal imaging using a novel fiber-based light source and scientific-grade CCD. A schematic of the camera is shown in Fig. 1.

Fig. 1. (Left) Layout of the adaptive optics retina camera. The camera consists of three sub-systems: (1) AO for correction of ocular aberrations, (2) pupil retro-illumination and fixation channels for alignment of the subject’s eye, and (3) retinal imaging using a scientific-grade CCD and flood illumination light sources consisting of an SLD and laser diode cascaded with multimode fibers. Details of the camera are included in the text. (Inset) SLD light launched into the multimode fiber is distributed among the fiber modes that propagate along the fiber length at different velocities and reduce the spatial coherence of the SLD light.

The second source is a stock 200 mW multi-mode laser diode (λ=670 nm). The spectral bandwidth of the diode was not provided by the manufacturer, but its temporal coherence length, after the multimode fiber, was measured at about 250 µm in air. This corresponds to a spectral bandwidth of approximately 0.8 nm. Owing to the significantly narrower spectral bandwidth, the laser diode was coupled to a much longer (300 meters) and higher NA multimode step index optical fiber (Lucent Technologies). The fiber has a numerical aperture (NA) of 0.39, core diameter of 200 µm, and core refractive index (ncore) of 1.457. Light exiting the two fibers were directed into the subject’s eye where the SLD flood illuminated a 1° patch of retina and the laser diode a 1.8° patch. The tips of the fibers were conjugate to the subject’s retina. To achieve improved SLD beam uniformity, a fiber mode scrambler was attached to the multimode fiber for some of the eyes examined. Exposure duration, light intensity, and delay between consecutive images were computer controlled.

A back-illuminated scientific-grade 12 bit CCD (Quantix 57, Ropier Scientific, Inc.) captured aerial images of the retina whose acquisition was synchronized to the strobing SLD and laser diode. The CCD array was 1056x530 pixels and consisted of a light-sensitive region of 512×530 pixels plus a similar storage area underneath the frame transfer mask. Custom dielectric beamsplitters were designed to reflect and transmit the corresponding flood illumination (670 and 679 nm) and SHWS (788 nm) wavelengths. This allowed simultaneously wavefront correction and retinal imaging without loss or mixing of light. The chromatic aberration of the eye caused a shift in focus between the two wavelengths that was offset by axially translating the Quantix CCD camera.

2.2 Human subjects

Retinal images were collected on five subjects (19 to 39 years of age) that were free of ocular disease and had normal corrected vision. Spectacle sphere and cylinder, which were obtained by a professional subjective refraction, ranged from -2.0 to -2.25 and 0 to -1.5 diopters, respectively.

The subjects’ line of sight was centered along the optical axis of the retina camera with the aid of a fixation target, bite bar stage, and video camera that monitored the subjects’ pupil in retro-illumination. The fixation target was located at the subjects’ far point and consisted of high contrast cross hairs positioned on a rectilinear grid 0.5 deg apart. The target was back illuminated with uniform red light. As shown in Fig. 1, the target is positioned in the illumination channel and is therefore not viewed through the AO path. A dental impression attached to a sturdy xyz bite bar translation stage stabilized the head and provided accurate pupil positioning. Retro-illumination of the pupil was realized with the 788 nm SLD.

The subjects were cyclopleged and their pupils dilated using two drops of Tropicamide 1% that were administered prior to measurements and one drop every hour thereafter. A single drop of Phenylephrine Hydrochloride 2.5% was also applied at the beginning of the measurements if additional dilation was needed. Data collection on each subject typically lasted one to two hours.

Sphere (defocus) and cylinder (astigmatism) were minimized in terms of the measured wavefront RMS by inserting appropriate trial lenses at the spectacle plane. Residual defocus and astigmatism associated with quantization of spectacle lens power (0.25 D) and subjective criterion for optimum focus in the presence of higher-order aberrations [27

27. L. N. Thibos, X. Hong, A. Bradley, and R. A. Applegate, “Accuracy and precision of methods to predict the results of subjective refraction from monochromatic wavefront aberration maps,” J. Vis. 4, 329–351 (2004). [PubMed]

] were corrected with the AO system.

Fig. 2. Measured RMS wavefront error traces with and without a real-time software filter that suppresses erroneous SHWS measurements, such as those caused by eye blinks. Note the stability of the RMS wavefront error immediately following each blink (as indicated by the black arrows) when the filter is employed compared to when it is not.

2.3 Retinal imaging at continuous frame rates

Videos were collected of the subjects’ retinas at continuous rates of 10, 30, and 60 Hz. The higher rates were achieved by sacrificing field of view, which was necessary as camera speed was limited by the Quantix readout rate. Specifically 10 Hz (full frame) provided a 1.8 degree field of view; 30 Hz a 0.8 degree; and 60 Hz a 0.4 degree. For all three patch sizes, sampling of the CCD pixels at the retina (1.1 µm/pixel) and illumination patch size (1.8 degree) were held fixed. Exposure times were 1 or 2 msec. To assess the utility of the retina camera for quick focusing and surveying the microscopic retina, videos were collected of the cone mosaic, the retinal vasculature, and through focus of the entire retina thickness. Videos were captured at 1.4 to 2.5 degrees retinal eccentricities. For the through focus videos, focusing was achieved by translating the Quantix CCD parallel to the retina camera’s optical axis.

2.4 Retinal imaging at short-burst frame rates

Acquisition of a finite number of images at very high rates was explored using the kinetics mode of the Quantix CCD, a method which we will refer to as short-burst imaging. In this mode, the CCD array was used as a temporary storage of four (256×530 pixels) and eight (128x530 pixels) images. The illuminated area of the CCD was controlled by a micrometer-adjusted mask (razor blade) that was positioned immediately upstream of the CCD in a conjugate plane. The timing diagram in Fig. 3 illustrates the temporal sequence of the short-burst imaging. Control software was developed that permitted image acquisition rates up to 500 Hz. At this rate, the exposure and delay durations were each 1 msec with four and eight images acquired in 7 and 15 msec, respectively.

Fig. 3. Temporal sequence for rapidly collecting (top) four and (bottom) eight images realized by temporarily storing the images on the CCD array. After each exposure, the electron charge on the CCD was rapidly shifted down columns to an unexposed (masked) region of the array in less than 100 µsec. This process was repeated after each additional exposure with the last exposure followed by a read out of the entire CCD array at a rate that minimized read noise.

To evaluate short-burst imaging, we focused our attention on the dynamic behavior of the capillary bed that defines the edge of the foveal avascular zone. As the exposure and time delay for the image bursts (synched to the strobing light source) are software controlled, it was straightforward to adjust these parameters to optimize viewing of cellular flow in capillaries. To this end, image bursts were collected with exposures ranging from 1 to 4 msec and delays from 1 to 40 msec.

Burst images were obtained without adaptive compensation by flattening the deformable mirror and translating the science camera to the plane that yielded the sharpest image of the capillaries. Burst images were also obtained with adaptive compensation and best focusing of the science camera. To account for fluctuations in accommodation not corrected by the AO, 10 separate image bursts were acquired with one second pauses between bursts (see Fig. 3). From the two sets (with and without AO) of 10 bursts, the sharpest images of the capillaries were selected for the two cases. Blood flow velocity was measured in several of the capillaries by directly mapping the movement of individual cells in the four or eight images.

2.5 Determining optimal exposure duration

Flood illuminated videos of the same patch of cone photoreceptors centered at either 1 or 1.4 degree eccentricity in two subjects were acquired with adaptive compensation and with exposure durations ranging from 1/3 msec to 100 msec. At the start of the experiment, one of the subjects was well acclimated to the instrument and the fixating task. For the other, we observed his accuracy to fixate during imaging improved and eventually plateaued after several trial runs. These initial runs were discarded. The ordering sequence of the eight trials (each with a different exposure duration) was randomized without the subjects’ knowledge. The power level of the 670 nm laser diode was adjusted so that the total energy per exposure duration was held approximately constant, except for the shortest two exposures (1/3 and 1 msec) in which the SLD reached its maximum. Power spectra were computed from the first 20 frames of each cone mosaic video and then averaged to increase signal to noise. Comparison of the normalized average power spectra permitted a straightforward means to quantify the impact of motion blur as a function of exposure duration.

3. Results

3.1 Wavefront correction

Figure 4 shows specific RMS wavefront errors measured across a 6.8-mm pupil during the retinal imaging experiments, averaged over three subjects, with and without AO correction. The two subjects not included had comparable RMS errors. The error is displayed in terms of the total error (2nd through 10th order aberrations), Zernike defocus (c4), two Zernike astigmatism terms (c3 and c5), and the higher order aberrations (3rd through 10th order aberrations). As indicated in the figure, AO decreased the total RMS error by more than an average factor of 7, with an average residual corrected error of 0.13 µm. It is interesting to note that the majority of residual wavefront error, after correction, is due to contributions of higher order (3rd through 10th) aberrations. For the experiments, the total RMS wavefront error during dynamic correction varied between 0.07 and 0.21 µm.

Figure 4 illustrates the overall effectiveness of the AO system to correct ocular aberrations, but it does not reflect some of the software advancements that go beyond basic AO control and that were utilized for the experiments in this paper. We found these additions helpful for diagnosing AO problems, optimizing system performance, and efficiently operating the system for the eye. These include image sharpening, temporal power spectra analysis, power rejection curves of the closed-loop AO system, time stamping of SHWS measurements, extensive logging, and improving corrector stability. A detailed description of these can be found elsewhere [28

28. Y. Zhang, J. Rha, R. S. Jonnal, and D. T. Miller, “Indiana University AO-OCT system,” in Adaptive Optics for Vision Science: Principles, Practices, Design, and Applications, J. Porter, et al., eds. (John Wiley & Sons, New Jersey, In Press).

]. As described in this citation, the cutoff frequency of the AO system (the frequency at which the rejection curve attains a value of 1) was found to be 0.87 Hz, indicating that aberrations with temporal frequencies below 0.87 Hz are reduced by the system, while those above 0.87 Hz are amplified.

Fig. 4. Average RMS wavefront error across a 6.8-mm pupil, measured in three subjects, with (dark gray) and without (light gray) AO compensation. RMS wavefront error is shown for the total aberrations (2nd through 10th order), Zernike defocus (C4), two Zernike astigmatism modes (C3 and C5), and higher order aberrations (3rd through 10th order). Error bars represent ± one standard deviation from the mean.

3.2 Effectiveness of the multimode fiber for reducing speckle noise

Figure 5 illustrates the extent to which the multimode fiber attenuates speckle noise in the SLD illumination. Shown are flood-illuminated images of essentially the same patch of cone photoreceptors in one subject’s eye with and without the fiber modification. Both images were collected with adaptive compensation and followed the same experimental protocol. The exit pupil was 6 mm. Images are representative of what we routinely observe in the laboratory. Note the mottled appearance in the left image that is characteristic of speckle and which completely masks photoreceptor information. The right image was obtained with the fiber and reveals a regular pattern of bright spots, which represent light exiting individual cone photoreceptors. Speckle noise is not visually evident indicating a strong reduction of the SLD spatial coherence by the fiber.

Fig. 5. Images of approximately the same patch of cone photoreceptors in one subject’s eye (left) with and (right) without the SLD beam passing through the 25 m multi-mode optical fiber. Note the absence of speckle in the right image allowing the cone mosaic to be easily observed.

As further supportive evidence of the reduction of speckle noise, Fig. 6 shows single one msec snapshots with the camera focused on the cone mosaic for one subject with and without AO correction. Sharpness of the bright spots was optimized by axially translating the science CCD camera. Note the substantial gain in contrast and clarity afforded by correcting the most significant wave aberrations of the eye. Row spacing of the bright spots (=center-to-center spacing * cos30°) ranges from 4.2 to 5.55 µm along a meridian that intercepts the foveal center (which is located below and to the right of the image). This range is consistent with anatomical and psychophysical estimates of cone spacing for this location [29

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

,30

30. D. R. Williams, “Topography of the foveal cone mosaic in the living human eye,” Vision Res. 28, 433–454, 1988. [CrossRef] [PubMed]

]. Note that our conversion from angular to linear retinal size is based on 300 µm/degree. For this particular subject (Fig. 6), a conversion of 299 µm/degree was determined from axial length measurements using ultrasonography [31

31. A. G. Bennett, A. R. Rudnicka, and D. F. Edgar, “Improvements on Littmann’s method of determining the size of retinal features by fundus photography,” Graefes Arch. Clin. Exp. Ophthalmol. , 232, 361–367 (1994). [CrossRef] [PubMed]

]. This approach has an expected error of ±10 microns (±3.4%). Speckle is an unlikely source of these bright spots as the spots are of uniform size and arranged in a regular pattern. Furthermore, the theoretical average speckle size (1.22λf/d) for a 6 mm pupil is 2.3 µm, which is noticeably smaller than the spacing of the observed bright spots (4.2 to 5.55 µm). The fact that granular structure of about 2.3 µm is not visually evident is additional evidence of the effectiveness of the multimode fiber to reduce speckle contrast (see fiber description in Section 2). Both uncorrected and corrected images are typical of cone images obtained using conventional incoherent light sources (flash and arc lamps) [2

2. 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]

5

5. A. V. Larichev, P. V. Ivanov, N. G. Iroshnikov, V. I. Shmalhauzen, and L. J. Otten, “Adaptive system for eye-fundus imaging,” Quantum Electron. 32, 902–908, 2002. [CrossRef]

,7

7. M. Glanc, E. Gendron, F. Lacombe, D. Lafaille, J.-F. Le Gargasson, and P. Léna, “Towards wide-field retinal imaging with adaptive optics,” Opt. Commun. 230, 225–238 (2004). [CrossRef]

,8

8. P. Fournier, G. R. G. Erry, L. J. Otten, A. Larichev, and N. Irochnikov, “Next generation high resolution adaptive optics fundus imager,” in 5th International Workshop on Adaptive Optics for Industry and Medicine, edited by Wenhan Jiang, Proceedings of SPIE Vol. 6018 (SPIE, Bellingham, WA, 2005).

].

Fig. 6. Individual raw conventional flood illuminated images of the cone mosaic centered at 1.25 deg. eccentricity in one subject’s eye (left) without and (right) with adaptive compensation. For both images, best correction of defocus and astigmatism was achieved with trial lenses and axial translation of the science CCD camera. The 1 deg patch of retina was illuminated by the 679 nm SLD after passing through the 25 m multimode fiber.

3.3 Retinal imaging at continuous frame rates

Figure 7 shows a 10 Hz video acquired before and during adaptive compensation. The video is of a fixating eye with the science camera focused to visually maximize sharpness of cone photoreceptor cells. After AO compensation begins, which takes about 4 frames to reach full compensation, punctuated bright spots a few microns in diameter are observed across the entire 1.8° field of view and correspond to individual cone cells. A number of the cones appear noticeably brighter and are relatively easy to follow through the video. Darkened hazy sub-regions (usually a few cones in diameter) are likely the shadow patterns of small retinal vessels projected onto the underlying mosaic. The video qualitatively illustrates the improvement in resolution and contrast that accrues when the AO system compensates for the aberrations of the eye including residual defocus and astigmatism. Note however that even at 10 Hz the video appears somewhat choppy owing to involuntary lateral movement of the retina between consecutive frames even though the subject was fixating at a single location.

Fig. 7. Raw 10 Hz flood illuminated video of the cone mosaic in one subject before and during adaptive compensation. The video was captured at 10 Hz with adaptive compensation occurring simultaneously at 15 Hz. The video runs at 10 Hz. The illumination patch subtends 1.8° at 1.4° eccentricity. Exposure duration is 2 msec. Illumination was provided by the 670 nm laser diode after passing through the 300 m multimode fiber. (1.1 MB)

The three AO compensated 30 Hz videos in Fig. 8 show the cone mosaic, retinal vasculature, and a through focus of the entire retina thickness. Illumination for these was provided by the 670 nm laser diode after passing through the 300 m multimode fiber. In the left video, individual cone cells fill the entire 0.8° field of view. The higher imaging rate (30 Hz compared to 10 Hz) clearly improves visual continuity of the cone mosaic, which is moving between frames. Note the retinal capillaries that traverse diagonally through the top one third of the frame. The capillaries are out of focus and largely transparent, but are made apparent by the cellular motion within them. This motion is not captured by individual frames and illustrates a clear advantage of video rate imaging.

This advantage is better illustrated by the center video in Fig. 8 that shows the camera focused on a network of retinal vessels and capillaries located in the inner retina. Two large vessels roughly 14.5 µm in diameter extend downward and branch into a complex web of small capillaries that are ~5 µm in diameter and typical of the smallest vessels in the retina. Many of the capillaries are well defined, albeit of low contrast due to their high transparency at the 670 nm illumination wavelength. In general, the capillaries are much easier to detect in the video than in individual still frames. Instrument resolution and sensitivity with AO is found sufficient to reveal the dynamic behavior of highly structured reflections from within capillaries, being approximately on the same scale size as individual blood cells (leukocytes and erythrocytes) and other microscopic blood constituents (platelets, plasma). Here we have assumed that the detected reflection is from within the vessel rather than at the exterior vessel surface. If our interpretation is correct, this may permit a direct means of non-invasively identifying blood composition at the cellular level in the smallest retinal vessels.

The right video in Fig. 8 depicts a through focus of the retina that was acquired at increasing depths, starting at the retinal vasculature and ending at the photoreceptor layer. In an attempt to remove the motion artifacts (which were comparable in magnitude to that present in the first two videos of Fig. 8), adjacent frames in the through focus video were registered using a cross correlation algorithm. Because of the significant variation in retinal information across the video, registration did not reach pixel accuracy, however, as can be seen in the video most retina motion was effectively removed. This registration was found to permit easier visual analysis of the video. Well defined capillaries are visible at the beginning of the video. The underlying cone photoreceptors are well out of focus. As the video progresses, the capillaries transform into faint shadows that project onto the underlying cone mosaic in the last few frames. The ability of these largely transparent vessels to generate shadows suggests a form of scintillation caused by a change in refractive index either within the vessel or between the vessel and surrounding neural tissue. Most of the vasculature observed in the video are small capillaries approximately 5–7 µm in diameter.

It is interesting to note the dynamic behavior of the bright single cone in the middle of the frame that lies directly behind a large capillary. The intensity of this cone appears to fluctuate rapidly with the capillaries in focus, presumably caused by cellular flow in the capillary, but then becomes reasonably stable with the cone in focus. This suggests that for cone imaging experiments that rely on accurate reflectance measurements special care should be taken to account for the optical impact of overlying capillaries. Also note that capillaries are observed at different depths in the retina with some vessels at best focus in the first few frames and others at best focus later in the video. This general observation of a stratified vasculature parallels histology [32

32. M. Iwasaki and H. Inomata, “Relation between superficial capillaries and foveal structures in the human retina,” Invest. Ophthalmol. Visual Sci. 27, 1698–1705 (1986).

] and recent results with optical coherence tomography [33

33. B. Cense, N. A. Nassif, T. C. Chen, M. C. Pierce, S. Yun, B. H. Park, B. E. Bouma, G. J. Tearney, and J. F. de Boer, “Ultrahigh-resolution high-speed retinal imaging using spectral-domain optical coherence tomography,” Opt. Express 12, 2435–2447 (2004). [CrossRef] [PubMed]

,14

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

]. AO flood illumination might represent a potentially straightforward and non-invasive approach to quickly map the retinal capillary network in three dimensions.

Fig. 8. Raw 30 Hz flood illuminated videos with adaptive compensation of (left) the cone mosaic, (middle) retinal vasculature, and (right) axial through focus of the retina. The illumination patch subtended 0.8°×0.8° (left, middle) and 0.67°×0.57° (right) at 1.4° (left), 2.5° (middle), and 1.25° (right) eccentricity (right). All videos were captured at 30 Hz with adaptive compensation occurring simultaneously at 15 (left) and 22 (middle, right) Hz. Frames of the through focus video were registered, which reduced the displayed field of view. The videos run at 30 Hz. Exposure duration is 2 (left) and 1 (middle, right) msec. Illumination was provided by the 670 nm laser diode after passing through the 300 meter multimode fiber. Scale bars represent 50 µm. (1.5 MB, 1.1 MB, 2.5 MB)

The AO compensated 60 Hz videos in Fig. 9 show small 0.4° patches of the cone mosaic and retinal vasculature. Illumination was again provided by the 670 nm laser diode and multimode fiber. Signal to noise in the 30 (Fig. 8) and 60 Hz videos is essentially identical as the retinal illumination, exposure duration, and CCD read noise remained unchanged for the two cases. In the left video, individual cone cells fill the entire 0.4° field of view. In comparison to the corresponding 30 Hz video in Fig. 8, cone clarity in this faster video is actually higher, though this must be attributed to better AO compensation as all other aspects of the two imaging experiments were essentially identical. The middle and right videos are identical with the right running four times slower to permit better visualization of the cellular blood flow. The video shows a small portion of a large vessel lying adjacent to a small one, both of which traverse diagonally through the frame. Even at the 60 Hz frame rate, the direction of flow in the vessels is not readily obvious even though the flow itself is quite apparent. We do not believe this confusion is due to temporal aliasing. While the frame size is small, being only 120 µm wide, a blood cell traveling at 1.5 mm/sec (a typical velocity) will move only 25 µm per frame and therefore require almost 5 frames to traverse the full frame width. For reasons we do not fully understand, punctuated bright reflections within the vessels (which should correspond to individual cells) could not be tracked across more than two or three frames. Perhaps the reflective properties of the cells change as the cells propagate and re-orient themselves within the confines of the vessels. In support of this, some frames contain highly punctuated and bright reflections (e.g., #50 and #81) that essentially vanish in the adjacent frames, i.e., within ±16.7 msec.

Fig. 9. 60 Hz flood illuminated videos with adaptive compensation of (left) the cone mosaic, and (middle, right) retinal vasculature. The illumination patch subtended 0.4° at 1.4° (left) and 2.5° (middle, right) eccentricity. All videos were captured at 60 Hz with adaptive compensation occurring simultaneously at 15 (left) and 22 (middle, right) Hz. The videos run at 30 (left, middle) Hz. The right video is identical to the middle video but runs four times slower at 7.5 Hz. Exposure duration is 2 (left) and 1 (middle, right) msec. Illumination was provided by the 670 nm laser diode after passing through the 300 m multimode fiber. Scale bars represent 25 µm. (1.0 MB, 0.5 MB, 0.5 MB)

While dynamic fluctuations in the reflectance of single cones have already been reported, these have occurred over periods of minutes to many hours in the living eye [34

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

,35

35. A. Pallikaris, D. R. Williams, and H. Hofer, “The Reflectance of Single Cones in the Living Human Eye”, Invest. Ophthalmol. Visual Sci. 44, 4580–4592 (2003). [CrossRef]

]. The fluctuations observed here are on a surprisingly much shorter time scale (seconds), which were easily revealed by the high speed acquisition of our retina camera. One possible explanation, which we are exploring [19

19. J. Rha, R. S. Jonnal, Y. Zhang, and D. T. Miller, “Rapid fluctuation in the reflectance of single cones and its dependence on photopigment bleaching,” Invest. Ophthalmol. Visual Sci. 46, E-Abstract 3546 (2005).

], is that the light exiting individual cone photoreceptors originates from reflections both in front and behind the outer segments. Interference of these reflections coupled with a change in the optical path length of the outer segment (due to photopigment bleaching by the imaging light source) could in principle generate temporally fast oscillations. We are developing an optical model of the photoreceptors that will explain these observations.

Fig. 10. Representative video acquired at 30 Hz in a dark adapted eye. Individual cone photoreceptors in the color-coded boxes (right) were extracted from the video. The video runs at 30 Hz. Exposure duration is 2 msec. Illumination was provided by the 670 nm laser diode after passing through the 300 meter multimode fiber. (2.3 MB)

3.4 Retinal imaging at short- burst frame rates

Fig. 11. Four-burst videos (top) without and (bottom) with adaptive compensation of a network of retinal capillaries at 1.4° eccentricity in subject RJ. The size of the retinal patch is 1 by 1/2 deg. Both videos were captured at 500 Hz using a 1 msec exposure and 1 msec delay. The videos play at 8 Hz, which is 62.5 times slower than the actual acquired rate. Due to the brevity of the videos, they are best viewed in loop mode in which the video automatically cycles. (2.3 MB)

Figure 12 demonstrates an eight-burst 500 Hz video on another subject. The AO correction is not as good as in the other videos, but illustrates that longer burst trains are readily possible at the expense of a reduced vertical field of view, in this case by a factor of two relative to the four-burst videos shown in Fig. 11.

Fig. 12. Eight-burst video with adaptive compensation that shows a network of retinal capillaries. Retinal eccentricity is 1.6°. The size of the retinal patch is 1 by 1/4 deg. Video was captured at 500 Hz using a 1 msec exposure and 1 msec delay. The video plays at 8 Hz. (0.5MB)

Leukocyte flow in parafoveal capillaries has already been reported using a 30 Hz SLO equipped with AO and a 660 nm light source [37

37. J. A. Martin and A. Roorda, “Direct and noninvaisve assessment of parafoveal capillary leukocyte velocity,” Ophthalmology 112, 2219–2224 (2005). [CrossRef] [PubMed]

]. While the flood illumination camera described here also uses AO and operates at a similar wavelength, the appearance of the videos from the two instruments are strikingly different. Capillary clarity and cellular contents appear better defined, and the underlying bright cone mosaic less distracting with flood illumination. Flood illumination also reveals cellular structure across the full extent of the capillaries (e.g. Fig. 11), thus permitting velocity measurements of many different cells in the same capillary.

3.5 Determining optimal exposure duration

Flood illuminated videos of the same patch of cone photoreceptors were acquired on two subjects with adaptive compensation and with exposure durations ranging from 1/3 msec to 100 msec. Illumination for these was provided by the 670 nm laser diode after passing through the 300 m multimode fiber. As representative examples of the acquired raw data, Fig. 13 displays a collage of four cone videos with exposure durations of 1, 10, 33, and 100 msec. As indicated in the figure, the frame rate varied between videos owing to the different exposure durations. From visual inspection, 1 and 10 msec exposures (left two videos) capture the fine granular structure of the cone mosaic in almost every frame. This suggests that blur from involuntary retina motion is minimal across these short exposures. For the longer 50 µm exposures of 33 msec (middle right) and 100 msec (rightmost), cone quality is significantly worse and in many frames is essentially lost suggesting that retina motion blur is the limiting factor. Interestingly however even at 100 msec, some cone structure can be observed in frames that coincide with what appears to be the end of a retinal movement, at which point the retina momentarily comes to rest. Even in these frames though, cone quality does not reach that found in the 1/3 msec and 10 msec videos.

As a means to quantify the impact of motion blur on image quality, Fig. 14 (left) shows the computed average power spectra for one of the two subjects at each of the eight exposures durations examined. Results from the other subject were similar. Power spectra are normalized to one at zero frequency and plotted using a log ordinate. While cone photoreceptors are visible in the Fig. 13 videos, no corresponding cusp in the power spectra (Fig. 14) is readily evident. This is likely attributable to the sampling of different retinal patches due to eye motion during the video. As shown in the figure, spectra for exposure durations from 1/3 to 10 msec contain approximately similar energy at frequencies up to about 100 cycles/deg. Above this the shorter 1/3 and 1 msec curves deviate towards higher noise floors that are attributed to their lower optical energy per flash. In principle the 1/3 msec exposure should be least corrupted by motion blur and therefore provide the most energy at any given spatial frequency. As shown in Fig. 14, however, other exposures (1, 4, and 10 msec) sometimes yield slightly more energy. We attribute this to differences in the quality of the AO correction, the refractive state of the eye, and the subjects’ ability to fixate. These sources of noise reflect the accuracy of the experiment. Nevertheless, Fig. 14 (left) reveals a clear trend in which longer exposures (>10 msec) lead to lower energy, in particular between 20 and 90 cycles/deg. Power is noticeably lowest for the longest exposure of 100 msec. Exposures less than 10 msec produce similar power curves suggesting movement of the retina is either negligible for these short times or at least within the error of the experiment.

Fig. 13. Representative flood illuminated videos of the same proximal patch of cone photoreceptors in the same subject with adaptive compensation and four different exposure durations. (2.3 MB)

To further quantify the impact of exposure duration, Fig. 14 (right) shows the ratio of the 4 msec power curve to each of the others. The ratios are averaged across both subjects. The 4 msec curve was chosen as it represents the shortest exposure at which the total energy per flash was not compromised by flash duration. As before, exposures up through 10 msec produce similar ratios, which again suggest that eye motion is negligible over these exposures. Exposures greater than 10 msec show a monotonic increase in the ratio and illustrate a clear benefit of short exposures (<10 msec). Power of the 4 msec exposure is more than a factor of three higher across a broad range of frequencies compared to that of the longest exposure (100 msec). As expected, the 4 msec exposure shows smaller gains when compared to the other exposures (20, 33, and 66 msec) with the gains localized to higher frequencies (between 70 and 80 cycles/deg). For comparison, the fundamental spatial frequency of the cone photoreceptors in the patches of retina imaged ranged from 60 to 75 cycles/degree.

These preliminary findings on two normal subjects suggest that AO flood-illumination retina cameras should operate with an exposure duration less than about 10 msec so as to minimize motion blur. This should be considered an upper threshold as the necessary exposure depends strongly on the subject’s ability to fixate, which can be noticeably worse in the aged or diseased eye.

4. Conclusion

Current adaptive optics flood-illumination retina cameras operate at low frame rates and employ bulky and expensive arc and flash lamp sources. As an alternative, we investigate a novel AO flood-illumination camera that achieves significantly higher frame rates using a current-modulated SLD and multimode laser diode coupled to a stretch of multimode optical fiber. Retinal images were successfully collected with exposure durations as short as 1/3 msec. Continuous frame rates of 10, 30, and 60 Hz were achieved for imaging 1.8, 0.8, and 0.4 deg retinal patches, respectively. In all cases, readout speed of the CCD limited frame rate. Through focus of the retina with the camera clearly revealed cellular details at both the photoreceptor and retinal vasculature layers. Little could be observed in the highly transparent neural tissue lying in between, illustrating a significant weakness of flood illumination compared to optical sectioning instruments such as OCT. Short-burst imaging up to 500 Hz was also achieved by temporarily storing sequences of images on the CCD. The 60 Hz (continuous) and 500 Hz (burst) frame rates are 9 and 75 times higher than the 6.7 Hz upper limit [7

7. M. Glanc, E. Gendron, F. Lacombe, D. Lafaille, J.-F. Le Gargasson, and P. Léna, “Towards wide-field retinal imaging with adaptive optics,” Opt. Commun. 230, 225–238 (2004). [CrossRef]

] of current AO flood-illumination retina cameras.

Fig. 14. (left) Radially-averaged power spectra of the same proximal patch of cones in 20 consecutive video frames for exposure durations of 1/3, 1, 4, 10, 20, 33, 66, and 100 msec. (right) Power ratio is shown averaged across the two subjects and for each of the examined exposure durations. Ratio is defined as power for the 4 msec exposure divided by that for a given exposure. The ratio quantifies the relative benefit of the 4 msec exposure.

Acknowledgments

The authors thank William Monette and Daniel Jackson’s group for electronics and machining support. A special thanks goes to Edgar Alvarez for early work on the power spectra analysis. Financial support was provided by the National Eye Institute grant 5R01 EY014743. This work was also supported in part by the National Science Foundation Science and Technology Center for Adaptive Optics, managed by the University of California at Santa Cruz under cooperative agreement No. AST-9876783.

References and links

1.

R. K. Tyson, Principles of Adaptive Optics (Academic Press, New York, 1998).

2.

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]

3.

H. Hofer, L. Chen, G. Y. Yoon, B. Singer, Y. Yamauchi, and D. R. Williams, “Improvement in retinal image quality with dynamic correction of the eye’s aberrations,” Opt. Express 8, 631–643 (2001). [CrossRef] [PubMed]

4.

N. Ling, Y. Zhang, X. Rao, X. Li, C. Wang, Y. Hu, and W. Jiang, “Small table-top adaptive optical systems for human retinal imaging”, in High-Resolution Wavefront Control: Methods, Devices, and Applications IV, J. D. Gonglewski, M. A. Vorontsov, M. T. Gruneisen, S. R. Restaino, and R. K. Tyson, eds., Proc. SPIE4825, 99–108 (2002). [CrossRef]

5.

A. V. Larichev, P. V. Ivanov, N. G. Iroshnikov, V. I. Shmalhauzen, and L. J. Otten, “Adaptive system for eye-fundus imaging,” Quantum Electron. 32, 902–908, 2002. [CrossRef]

6.

D. U. Bartsch, L. Zhu, P. C. Sun, S. Fainman, and W. R. Freeman, “Retinal imaging with a low-cost micromachined membrane deformable mirror,” J. Biomed. Opt. 7, 451–456 (2002). [CrossRef] [PubMed]

7.

M. Glanc, E. Gendron, F. Lacombe, D. Lafaille, J.-F. Le Gargasson, and P. Léna, “Towards wide-field retinal imaging with adaptive optics,” Opt. Commun. 230, 225–238 (2004). [CrossRef]

8.

P. Fournier, G. R. G. Erry, L. J. Otten, A. Larichev, and N. Irochnikov, “Next generation high resolution adaptive optics fundus imager,” in 5th International Workshop on Adaptive Optics for Industry and Medicine, edited by Wenhan Jiang, Proceedings of SPIE Vol. 6018 (SPIE, Bellingham, WA, 2005).

9.

A. W. Dreher, J. F. Bille, and R. N. Weinreb, “Active optical depth resolution improvement of the laser tomographic scanner,” Appl. Opt. 28, 804–808 (1989). [CrossRef] [PubMed]

10.

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

11.

D. T. Miller, J. Qu, R. S. Jonnal, and K. Thorn, “Coherence gating and adaptive optics in the eye,” in Coherence Domain Optical Methods and Optical Coherence Tomography in Biomedicine VII, V. V. Tuchin, J. A. Izatt, and J. G. Fujimoto, eds., Proc. SPIE4956, 65–72 (2003). [CrossRef]

12.

B. Hermann, E. J. Fernández, A. Unterhuber, H. Sattmann, A. F. Fercher, W. Drexler, P. M. Prieto, and P. Artal, “Adaptive-optics ultrahigh-resolution optical coherence tomography,” Opt. Lett. 29, 2142–2144 (2004). [CrossRef] [PubMed]

13.

Y. Zhang, J. Rha, R. Jonnal, and D. Miller, “Adaptive optics parallel spectral domain optical coherence tomography for imaging the living retina,” Opt. Express 13, 4792–4811 (2005). [CrossRef] [PubMed]

14.

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

15.

E. J. Fernández, B. Považay, B. Hermann, A. Unterhuber, H. Sattmann, P. M. Prieto, R. Leitgeb, P. Ahnelt, P. Artal, and W. Drexler W, “Three-dimensional adaptive optics ultrahigh-resolution optical coherence tomography using a liquid crystal spatial light modulator,” Vision Res. 45, 3432–3444 (2005). [CrossRef] [PubMed]

16.

L. A. Riggs, J. C. Armington, and J.C., “Motions of the retinal image during fixation,” J. Opt. Soc. Am. 44, 315–321 (1954). [CrossRef] [PubMed]

17.

I. Iglesias and P. Artal, “High-resolution retinal images obtained by deconvolution from wave-front sensing,” Opt. Lett. 25, 1804–1806 (2000). [CrossRef]

18.

K. E. Thorn, J. Qu, R. J. Jonnal, and D. T. Miller, “Adaptive optics flood-illuminated camera for high speed retinal imaging,” Invest. Ophthalmol. Visual Sci. 44, E-Abstract 1002 (2003).

19.

J. Rha, R. S. Jonnal, Y. Zhang, and D. T. Miller, “Rapid fluctuation in the reflectance of single cones and its dependence on photopigment bleaching,” Invest. Ophthalmol. Visual Sci. 46, E-Abstract 3546 (2005).

20.

K. E. Thorn, R. S. Jonnal, J. Qu, and D. T. Miller, “High-speed imaging of the retinal microvasculature with adaptive optics,” Society of Photo-Optical Instrumentation Engineers’ 2004 International Symposium on Ophthalmic Technologies XIV, San Jose, CA, January 24–25, 2004.

21.

J. Rha, R. S. Jonnal, Y. Zhang, and D. T. Miller, “Video rate imaging with a conventional flood illuminated adaptive optics retin,a camera,” 88th Optical Society of America Annual Meeting, Rochester, New York, October 10–14, 2004.

22.

ANSI, American National Standard for the Safe Use of Lasers, ANSI Z136.1 (Laser Institute of America, Orlando, FL, 2000).

23.

B. Crosignani, B. Diano, and P. Di Porto, “Speckle-pattern visibility of light transmitted through a multimode optical fiber,” J. Opt. Soc. Am. 66, 1312–1313 (1976). [CrossRef]

24.

B. Dingel and S. Kawata, “Laser-diode microscope with fiber illumination,” Opt. Commun. 93, 27–32 (1992). [CrossRef]

25.

E. G. Rawson, J. W. Goodman, and R. E. Norton, “Frequency dependence of modal noise in multimode optical fibers,” J. Opt. Soc. Am. 70, 968–976 (1980). [CrossRef]

26.

F. M. Mims III, A Practical Introduction to Lightwave Communications (Howard W. Sams & Co., Indiana, 1982).

27.

L. N. Thibos, X. Hong, A. Bradley, and R. A. Applegate, “Accuracy and precision of methods to predict the results of subjective refraction from monochromatic wavefront aberration maps,” J. Vis. 4, 329–351 (2004). [PubMed]

28.

Y. Zhang, J. Rha, R. S. Jonnal, and D. T. Miller, “Indiana University AO-OCT system,” in Adaptive Optics for Vision Science: Principles, Practices, Design, and Applications, J. Porter, et al., eds. (John Wiley & Sons, New Jersey, In Press).

29.

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

30.

D. R. Williams, “Topography of the foveal cone mosaic in the living human eye,” Vision Res. 28, 433–454, 1988. [CrossRef] [PubMed]

31.

A. G. Bennett, A. R. Rudnicka, and D. F. Edgar, “Improvements on Littmann’s method of determining the size of retinal features by fundus photography,” Graefes Arch. Clin. Exp. Ophthalmol. , 232, 361–367 (1994). [CrossRef] [PubMed]

32.

M. Iwasaki and H. Inomata, “Relation between superficial capillaries and foveal structures in the human retina,” Invest. Ophthalmol. Visual Sci. 27, 1698–1705 (1986).

33.

B. Cense, N. A. Nassif, T. C. Chen, M. C. Pierce, S. Yun, B. H. Park, B. E. Bouma, G. J. Tearney, and J. F. de Boer, “Ultrahigh-resolution high-speed retinal imaging using spectral-domain optical coherence tomography,” Opt. Express 12, 2435–2447 (2004). [CrossRef] [PubMed]

34.

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

35.

A. Pallikaris, D. R. Williams, and H. Hofer, “The Reflectance of Single Cones in the Living Human Eye”, Invest. Ophthalmol. Visual Sci. 44, 4580–4592 (2003). [CrossRef]

36.

H. Nishiwaki, Y. Ogura, H. Kimura, J. Kiryu, and Y. Honda, “Quantitative evaluation of leukocyte dynamics in retinal microcirculation,” Invest. Ophthalmol. Vis. Sci. 36, 123–130 (1995). [PubMed]

37.

J. A. Martin and A. Roorda, “Direct and noninvaisve assessment of parafoveal capillary leukocyte velocity,” Ophthalmology 112, 2219–2224 (2005). [CrossRef] [PubMed]

OCIS Codes
(010.1080) Atmospheric and oceanic optics : Active or adaptive optics
(060.2380) Fiber optics and optical communications : Fiber optics sources and detectors
(110.0180) Imaging systems : Microscopy
(330.4300) Vision, color, and visual optics : Vision system - noninvasive assessment
(330.5370) Vision, color, and visual optics : Physiological optics

ToC Category:
Vision, Color, and Visual Optics

History
Original Manuscript: February 21, 2006
Revised Manuscript: April 28, 2006
Manuscript Accepted: May 4, 2006
Published: May 15, 2006

Virtual Issues
Vol. 1, Iss. 6 Virtual Journal for Biomedical Optics

Citation
Jungtae Rha, Ravi S. Jonnal, Karen E. Thorn, Junle Qu, Yan Zhang, and Donald T. Miller, "Adaptive optics flood-illumination camera for high speed retinal imaging," Opt. Express 14, 4552-4569 (2006)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=oe-14-10-4552


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. R. K. Tyson, Principles of Adaptive Optics (Academic Press, New York, 1998).
  2. 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]
  3. H. Hofer, L. Chen, G. Y. Yoon, B. Singer, Y. Yamauchi, and D. R. Williams, "Improvement in retinal image quality with dynamic correction of the eye’s aberrations," Opt. Express 8, 631-643 (2001). [CrossRef] [PubMed]
  4. N. Ling, Y. Zhang, X. Rao, X. Li, C. Wang, Y. Hu, and W. Jiang, "Small table-top adaptive optical systems for human retinal imaging", in High-Resolution Wavefront Control: Methods, Devices, and Applications IV, J. D. Gonglewski, M. A. Vorontsov, M. T. Gruneisen, S. R. Restaino, R. K. Tyson, eds., Proc. SPIE 4825, 99-108 (2002). [CrossRef]
  5. A. V. Larichev, P. V. Ivanov, N. G. Iroshnikov, V. I. Shmalhauzen, L. J. Otten, "Adaptive system for eye-fundus imaging," Quantum Electron. 32, 902-908, 2002. [CrossRef]
  6. D. U. Bartsch, L. Zhu, P. C. Sun, S. Fainman, and W. R. Freeman, "Retinal imaging with a low-cost micromachined membrane deformable mirror," J. Biomed. Opt. 7, 451-456 (2002). [CrossRef] [PubMed]
  7. M. Glanc, E. Gendron, F. Lacombe, D. Lafaille, J.-F. Le Gargasson, and P. Léna, "Towards wide-field retinal imaging with adaptive optics," Opt. Commun. 230, 225-238 (2004). [CrossRef]
  8. P. Fournier, G. R. G. Erry, L. J. Otten, A. Larichev, N. Irochnikov, "Next generation high resolution adaptive optics fundus imager," in 5th International Workshop on Adaptive Optics for Industry and Medicine, edited by Wenhan Jiang, Proceedings of SPIE Vol. 6018 (SPIE, Bellingham, WA, 2005).
  9. A. W. Dreher, J. F. Bille, and R. N. Weinreb, "Active optical depth resolution improvement of the laser tomographic scanner," Appl. Opt. 28, 804-808 (1989). [CrossRef] [PubMed]
  10. A. Roorda, F. Romero-Borja, W. J. Donnelly, H. Queener, T. J. Hebert, and M. C. W. Campbell, "Adaptive optics scanning laser ophthalmoscopy," Opt. Express 10, 405-412 (2002). [PubMed]
  11. D. T. Miller, J. Qu, R. S. Jonnal and K. Thorn, "Coherence gating and adaptive optics in the eye," in Coherence Domain Optical Methods and Optical Coherence Tomography in Biomedicine VII, V. V. Tuchin, J. A. Izatt, J. G. Fujimoto, eds., Proc. SPIE 4956, 65-72 (2003). [CrossRef]
  12. B. Hermann, E. J. Fernández, A. Unterhuber, H. Sattmann, A. F. Fercher, W. Drexler, P. M. Prieto, and P. Artal, "Adaptive-optics ultrahigh-resolution optical coherence tomography," Opt. Lett. 29, 2142-2144 (2004). [CrossRef] [PubMed]
  13. Y. Zhang, J. Rha, R. Jonnal, and D. Miller, "Adaptive optics parallel spectral domain optical coherence tomography for imaging the living retina," Opt. Express 13, 4792-4811 (2005). [CrossRef] [PubMed]
  14. R. Zawadzki, S. Jones, S. Olivier, M. Zhao, B. Bower, J. Izatt, S. Choi, S. Laut, and J. Werner, "Adaptive-optics optical coherence tomography for high-resolution and high-speed 3D retinal in vivo imaging," Opt. Express 13, 8532-8546 (2005). [CrossRef] [PubMed]
  15. E. J. Fernández, B. Považay, B. Hermann, A. Unterhuber, H. Sattmann, P. M. Prieto, R. Leitgeb, P. Ahnelt, P. Artal, W. Drexler W, "Three-dimensional adaptive optics ultrahigh-resolution optical coherence tomography using a liquid crystal spatial light modulator," Vision Res. 45, 3432-3444 (2005). [CrossRef] [PubMed]
  16. L. A. Riggs and J. C. Armington, J.C., "Motions of the retinal image during fixation," J. Opt. Soc. Am. 44, 315-321 (1954). [CrossRef] [PubMed]
  17. I. Iglesias and P. Artal, "High-resolution retinal images obtained by deconvolution from wave-front sensing," Opt. Lett. 25, 1804-1806 (2000). [CrossRef]
  18. K. E. Thorn, J. Qu, R. J. Jonnal, and D. T. Miller, "Adaptive optics flood-illuminated camera for high speed retinal imaging," Invest. Ophthalmol. Visual Sci. 44, E-Abstract 1002 (2003).
  19. J. Rha, R. S. Jonnal, Y. Zhang, and D. T. Miller, "Rapid fluctuation in the reflectance of single cones and its dependence on photopigment bleaching," Invest. Ophthalmol. Visual Sci. 46, E-Abstract 3546 (2005).
  20. K. E. Thorn, R. S. Jonnal, J. Qu, and D. T. Miller, "High-speed imaging of the retinal microvasculature with adaptive optics," Society of Photo-Optical Instrumentation Engineers' 2004 International Symposium on Ophthalmic Technologies XIV, San Jose, CA, January 24-25, 2004.
  21. J. Rha, R. S. Jonnal, Y. Zhang and D. T. Miller, "Video rate imaging with a conventional flood illuminated adaptive optics retin,a camera," 88th Optical Society of America Annual Meeting, Rochester, New York, October 10-14, 2004.
  22. ANSI, American National Standard for the Safe Use of Lasers, ANSI Z136.1 (Laser Institute of America, Orlando, FL, 2000).
  23. B. Crosignani, B. Diano, and P. Di Porto, "Speckle-pattern visibility of light transmitted through a multimode optical fiber," J. Opt. Soc. Am. 66, 1312-1313 (1976). [CrossRef]
  24. B. Dingel and S. Kawata, "Laser-diode microscope with fiber illumination," Opt. Commun. 93, 27-32 (1992). [CrossRef]
  25. E. G. Rawson, J. W. Goodman, R. E. Norton, "Frequency dependence of modal noise in multimode optical fibers," J. Opt. Soc. Am. 70, 968-976 (1980). [CrossRef]
  26. F. M. MimsIII, A Practical Introduction to Lightwave Communications (Howard W. Sams & Co., Indiana, 1982).
  27. L. N. Thibos, X. Hong, A. Bradley, and R. A. Applegate, "Accuracy and precision of methods to predict the results of subjective refraction from monochromatic wavefront aberration maps," J. Vis. 4, 329-351 (2004). [PubMed]
  28. Y. Zhang, J. Rha, R. S. Jonnal, and D. T. Miller, "Indiana University AO-OCT system," in Adaptive Optics for Vision Science: Principles, Practices, Design, and Applications, J. Porter, et al., eds. (John Wiley & Sons, New Jersey, In Press).
  29. C. A. Curcio, K. R. Sloan, R. E. Kalina, and A. E. Hendrickson, "Human photoreceptor topography," J. Comp. Neurol. 292, 497-523 (1990). [CrossRef] [PubMed]
  30. D. R. Williams, "Topography of the foveal cone mosaic in the living human eye," Vision Res. 28, 433-454, 1988. [CrossRef] [PubMed]
  31. A. G. Bennett, A. R. Rudnicka, D. F. Edgar, "Improvements on Littmann’s method of determining the size of retinal features by fundus photography," Graefes Arch. Clin. Exp. Ophthalmol.,  232, 361-367 (1994). [CrossRef] [PubMed]
  32. M. Iwasaki and H. Inomata, "Relation between superficial capillaries and foveal structures in the human retina," Invest. Ophthalmol. Visual Sci. 27, 1698-1705 (1986).
  33. B. Cense, N. A. Nassif, T. C. Chen, M. C. Pierce, S. Yun, B. H. Park, B. E. Bouma, G. J. Tearney, and J. F. de Boer, "Ultrahigh-resolution high-speed retinal imaging using spectral-domain optical coherence tomography," Opt. Express 12, 2435-2447 (2004). [CrossRef] [PubMed]
  34. A. R. Wade, F. W. Fitzke, "In-vivo imaging of the human cone photoreceptor mosaic using a confocal LSO", Lasers Light Ophthalmol. 8, 129-136 (1998).
  35. A. Pallikaris, D. R. Williams, and H. Hofer, "The Reflectance of Single Cones in the Living Human Eye", Invest. Ophthalmol. Visual Sci. 44, 4580 - 4592 (2003). [CrossRef]
  36. H. Nishiwaki, Y. Ogura, H. Kimura, J. Kiryu, and Y. Honda, "Quantitative evaluation of leukocyte dynamics in retinal microcirculation," Invest. Ophthalmol. Vis. Sci. 36, 123-130 (1995). [PubMed]
  37. J. A. Martin and A. Roorda, "Direct and noninvaisve assessment of parafoveal capillary leukocyte velocity," Ophthalmology 112, 2219-2224 (2005). [CrossRef] [PubMed]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

Supplementary Material


» Media 1: AVI (1173 KB)     
» Media 2: AVI (1485 KB)     
» Media 3: AVI (1116 KB)     
» Media 4: AVI (2545 KB)     
» Media 5: AVI (1074 KB)     
» Media 6: AVI (534 KB)     
» Media 7: AVI (527 KB)     
» Media 8: AVI (2321 KB)     
» Media 9: AVI (2313 KB)     
» Media 10: AVI (512 KB)     
» Media 11: AVI (2371 KB)     

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited