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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editor: Gregory W. Faris
  • Vol. 4, Iss. 5 — May. 5, 2009
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Comparison of reflectivity maps and outer retinal topography in retinal disease by 3-D Fourier domain optical coherence tomography

Maciej Wojtkowski, Bartosz L. Sikorski, Iwona Gorczynska, Michalina Gora, Maciej Szkulmowski, Danuta Bukowska, Jakub Kałuzny, James G. Fujimoto, and Andrzej Kowalczyk  »View Author Affiliations


Optics Express, Vol. 17, Issue 5, pp. 4189-4207 (2009)
http://dx.doi.org/10.1364/OE.17.004189


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Abstract

We demonstrate and compare two image processing methods for visualization and analysis of three-dimensional optical coherence tomography (OCT) data acquired in eyes with different retinal pathologies. A method of retinal layer segmentation based on a multiple intensity thresholding algorithm was implemented in order to generate simultaneously outer retinal topography maps and reflectivity maps. We compare the applicability of the two methods to the diagnosis of retinal diseases and their progression. The data presented in this contribution were acquired with a high speed (25,000 A-scans/s), high resolution (4.5 µm) spectral OCT prototype instrument operating in the ophthalmology clinic.

© 2009 Optical Society of America

Data sets associated with this article are available at http://hdl.handle.net/10376/1219. Links such as View 1 that appear in figure captions and elsewhere will launch custom data views if ISP software is present.

1. Introduction

Optical coherence tomography (OCT) is an optical imaging technology, which at present has its most widespread application in the field of clinical ophthalmology. OCT, along with scanning laser ophthalmoscopy, scanning laser polarimetry, and other novel imaging methods, provides clinical information that previously was sought only with standard fundus photography and fluorescein angiography. Instruments based on OCT technology provide a wide range of imaging protocols and different tools for quantitative analysis of the retina, including mapping of the retinal thickness, measurement of nerve fiber layer (NFL) thickness, and optic nerve head (ONH) parameters.

OCT is based on an interferometric technique known as white light interferometry [1

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

]. In most OCT systems the measurements are performed using a Michelson interferometer with a light source of low coherence length. The light beam is split into two arms of the interferometer: one arm is terminated by a reference mirror and the second one by the object analyzed. There are two ways of detecting OCT interferometric signals: in time and in optical frequency domains. Time domain OCT (TdOCT) instruments use the reference arm delay line comprising a mechanical scanner. Interference between the light from the sample and the reference mirror occurs only when the distance travelled by light in both interferometer arms matches to within the coherence length. In classic OCT systems there are tradeoffs between detection sensitivity and imaging speed or axial image resolution. The Fourier domain detection method overcomes this limitation. In Fourier domain optical coherence tomography information about the internal structure of an object is retrieved from the interferometric signal detected as a function of optical frequencies [2

2. M. Wojtkowski, R. Leitgeb, A. Kowalczyk, T. Bajraszewski, and A. F. Fercher, “In vivo human retinal imaging by Fourier domain optical coherence tomography,” J. Biomed. Opt. 7, 457–463 (2002). [CrossRef] [PubMed]

]. This kind of interference pattern is called spectral fringe signal. Fourier domain OCT detection can be performed in two ways: spectral OCT (SOCT) also called spectral domain OCT and swept source OCT. SOCT uses a spectrometer with a high speed, multichannel photodetector and swept source OCT utilizes a rapidly tunable laser source and a single photodiode for the detection of the fringe pattern. Application of Fourier domain detection to OCT improves imaging speed and resolution, and yields significant improvement of OCT images [3

3. M. Wojtkowski, V. J. Srinivasan, T. H. Ko, J. G. Fujimoto, A. Kowalczyk, and J. S. Duker, “Ultrahighresolution high-speed Fourier domain optical coherence tomography and methods for dispersion compensation,” Opt. Express 12, 2404–2422 (2004). [CrossRef] [PubMed]

]. This enables development of new methods for quantitative analysis and visualization of retinal structure and pathology [4–6

4. 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, 2054–2065 (2006). [CrossRef] [PubMed]

].

Spectral optical coherence tomography allows high resolution and high speed imaging of human retina in vivo [3

3. M. Wojtkowski, V. J. Srinivasan, T. H. Ko, J. G. Fujimoto, A. Kowalczyk, and J. S. Duker, “Ultrahighresolution high-speed Fourier domain optical coherence tomography and methods for dispersion compensation,” Opt. Express 12, 2404–2422 (2004). [CrossRef] [PubMed]

, 4

4. 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, 2054–2065 (2006). [CrossRef] [PubMed]

, 7

7. R. A. Leitgeb, W. Drexler, A. Unterhuber, B. Hermann, T. Bajraszewski, T. Le, A. Stingl, and A. F. Fercher, “Ultrahigh resolution Fourier domain optical coherence tomography,” Opt. Express 12, 2156–2165 (2004). [CrossRef] [PubMed]

, 8

8. B. Cense, N. A. Nassif, T. C. Chen, M. C. Pierce, S.-H. 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]

]. New commercially available instruments based on spectral OCT technology can acquire 512 A-scans in 25 milliseconds. Therefore, dense raster scanning protocols can be implemented in these instruments, enabling acquisition of three-dimensional (3-D) data. The associated improvement in the coverage of the retina increases the probability of revealing focal pathological changes [5

5. M. Wojtkowski, V. Srinivasan, J. G. Fujimoto, T. Ko, J. S. Schuman, A. Kowalczyk, and J. S. Duker, “Three-dimensional retinal imaging with high-speed ultrahigh-resolution optical coherence tomography,” Ophthalmology 112, 1734–1746 (2005). [CrossRef] [PubMed]

]. Once collected, the 3-D data can serve as a reference for tracking disease progression or the healing process. This raises the question how to determine universal markers to allow fast and repeatable comparison of retinal images in long term studies. One of the most promising methods is quantitative analysis of outer retinal layers usually well reconstructed by OCT techniques.

In ophthalmology, a standard method of assessing retinal pathology consists in analyzing coronal plane oriented images. Therefore, the most desirable representation of 3-D OCT data are en face views of the retina. Such representation of OCT images was exploited by Podoleanu et al. and Hitzenberger et al. in their en-face OCT systems [20–22

20. A. G. Podoleanu, M. Seeger, G. M. Dobre, D. J. Webb, D. A. Jackson, and F. W. Fitzke, “Transversal and longitudinal images from the retina of the living eye using low coherence reflectometry,” J. Biomed. Opt. 3, 12–20 (1998). [CrossRef]

]. In these instruments images are collected by employing transversal priority scanning [23

23. A. G. Podoleanu and D. A. Jackson, “Combined optical coherence tomograph and scanning laser ophthalmoscope,” Electron. Lett. 34, 1088–1090 (1998). [CrossRef]

, 24

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

]. This technology also allows simultaneous measurements of en face OCT images and corresponding confocal ophthalmoscopic images along with cross-sectional OCT at specifiable locations on the confocal image [25

25. A. G. Podoleanu, G. M. Dobre, R. G. Cucu, R. Rosen, P. Garcia, J. Nieto, D. Will, R. Gentile, T. Muldoon, J. Walsh, L. A. Yannuzzi, Y. Fisher, D. Orlock, R. Weitz, J. A. Rogers, S. Dunne, and A. Boxer, “Combined multiplanar optical coherence tomography and confocal scanning ophthalmoscopy,” J. Biomed. Opt. 9, 86–93 (2004). [CrossRef] [PubMed]

]. Unfortunately, such manner of direct en face imaging creates many problems with correct interpretation of measured data. The plane of the retina at the fundus is not flat and this complicates considerably the interpretation of the sections of tissue in the images. This effect is even more severe in high resolution instruments, where the OCT en face slices are very thin (3 µm).

To overcome these problems and continue exploiting en face retinal views for diagnosis and monitoring disease progression, one can use high speed Fourier domain OCT, three dimensional retinal imaging. The curvature of the fundus can be thereby corrected numerically in post processing and en face images can be extracted from 3-D data. Here en face views can be reconstructed using two methods: qualitative mapping of the reflectivity changes in selected retinal layers and quantitative mapping of changes in retinal topography. Reflectivity maps are generated by axial summation of the 3-D OCT data. Summation over the entire depth of the dataset generates OCT fundus views [5

5. M. Wojtkowski, V. Srinivasan, J. G. Fujimoto, T. Ko, J. S. Schuman, A. Kowalczyk, and J. S. Duker, “Three-dimensional retinal imaging with high-speed ultrahigh-resolution optical coherence tomography,” Ophthalmology 112, 1734–1746 (2005). [CrossRef] [PubMed]

, 6

6. S. L. Jiao, R. Knighton, X. R. Huang, G. Gregori, and C. A. Puliafito, “Simultaneous acquisition of sectional and fundus ophthalmic images with spectral-domain optical coherence tomography,” Opt. Express 13, 444–452 (2005). [CrossRef] [PubMed]

, 26

26. I. Gorczynska, V. J. Srinivasan, L. N. Vuong, R. W. Chen, J. J. Liu, E. Reichel, M. Wojtkowski, J. S. Schuman, J. S. Duker, and J. G. Fujimoto, “Projection OCT fundus imaging for visualizing outer retinal pathology in non-exudative age related macular degeneration,” Br. J. Ophthalmol. (accepted 2008, electronic version available). [PubMed]

]. Unfortunately, information about subtle reflectivity changes in selected retinal layers is usually lost during such procedure. To retrieve this information, the summation should be performed in selected depth ranges corresponding to layers most prone to disease development. The anterior and posterior boundaries of a reflectivity map are selected relatively to a reference surface. Such a surface is defined by segmentation of one of the retinal anatomical layers (usually the RPE) and approximation of its normal shape by a smooth curve. Axial summation of the intensity within selected depth ranges rejects the signal from unwanted layers, thereby enhancing sensitivity to pathology localized in specific retinal layers [26

26. I. Gorczynska, V. J. Srinivasan, L. N. Vuong, R. W. Chen, J. J. Liu, E. Reichel, M. Wojtkowski, J. S. Schuman, J. S. Duker, and J. G. Fujimoto, “Projection OCT fundus imaging for visualizing outer retinal pathology in non-exudative age related macular degeneration,” Br. J. Ophthalmol. (accepted 2008, electronic version available). [PubMed]

, 27

27. B. L. Sikorski, M. Wojtkowski, J. J. Kaluzny, M. Szkulmowski, and A. Kowalczyk, “Correlation of spectral optical coherence tomography with fluorescein and indocyanine green angiography in multiple evanescent white dot syndrome,” Br. J. Ophthalmol. 92, 1552–1557 (2008). [CrossRef] [PubMed]

].

In this paper, we present an OCT data processing method which enables to obtain simultaneously reflectivity maps and retinal topography maps. Both methods are compared by analyzing three-dimensional OCT data acquired in eyes with retinal pathologies. To this end, five cases of different retinal diseases were selected out of 600 measured eyes. Three patients were followed up in time (up to 30 months). The presented results allow comparing of the two methods of analyzing retinal pathologies. We also show how both methods can be applied to the process of tracking the disease over time.

2. Materials and methods

2.1 OCT instrument and scanning protocols

All data presented in this contribution were obtained with the prototype high-resolution, high speed spectral OCT system constructed at the Institute of Physics of Nicolaus Copernicus University. The instrument has been used on an every-day basis in the ophthalmology clinic of the Collegium Medicum of Nicolaus Copernicus University in Bydgoszcz, Poland since October 2005. A schematic drawing of the spectral OCT system is shown in Fig. 1. In order to achieve the high axial imaging resolution of 4.5 µm we used a Broadlighter D830 light source (Superlum, Moscow) emitting partially coherent light from two coupled superluminescent diodes giving a total wavelength span of 70nm at full-width-half-maximum (L in Fig. 1b.). To ensure high portability and flexibility of the system, the SOCT instrument is based on optical fiber technology with fiber based Michelson interferometer. The detector (D, Fig. 1b.) is a custom made spectrometer comprising a line-scan camera and a volume holographic diffraction grating (1200 lines/mm, Wasatch Photonics). In order to collect three-dimensional data in clinical practice, the total acquisition time cannot exceed a few seconds.

Fig. 1. a. Schematic diagram of the spectral optical coherence tomography instrument. b. Photograph of the prototype SOCT instrument operating in the ophthalmology clinic.

This was achieved by using a high speed CCD line scan camera (AViiVA M2, Atmel), which enables acquisition of 25,000 axial lines (A-scans) per second preserving a high imaging sensitivity of 95dB. The entire interferometer (I, Fig. 1b.), and the scanning system, is mounted on an adjustable ophthalmic stand (S, Fig. 1b.). The acquisition process and scanning protocols are controlled by a custom designed electronic driving unit (E, Fig. 1b.). To reduce motion artifacts and to facilitate the examination process, either internal or external fixation light can be used. The optical power incident on the eye was 750 µW, consistent with Polish Norms and ANSI safety standards.

The imaging of patients was performed using four different scanning protocols for each measured eye. In order to gain general information about structural changes due to retinal disease, we collected 35 cross-sectional images, each consisting of 3,000 A-scans acquired in less than 4 seconds and covering an area of X=6 mm by Y=3 mm. Measurement of a 3 mm range in the superior-inferior direction was dictated by the requirement of a high quality OCT fundus image. This OCT fundus image, and all 35 cross-sections, can be brought into registration with fundus photographs and fluorescein angiographs by post-processing. To maximally enhance the image quality and sensitivity of OCT measurements we used another scan protocol, in which five cross-sectional images, 6,000 A-scans each, are acquired in the 9mm by 1mm area of the retina. The acquisition time is one second. This scan pattern is especially useful in patients with media opacities which may severely suppress the OCT signal. Use of 6,000 A-scans to construct an OCT cross-sectional image, can significantly improve the OCT image and more detailed retinal structure can be revealed. Additionally, the high definition images can be used as representative examples of the examined pathology. They are useful for illustrative purposes. The two remaining scanning protocols implemented in our instrument provide three-dimensional data for quantitative analysis. Both measure the same number (200) of cross-sectional images, 400 A-scans each, within 3 seconds. One covers a 6mm by 6mm and the other 4mm×4mm area of the retina resulting in lateral resolution of 15µm by 30 µm in the first case and 10µm by 20 µm in the second protocol. The scanning is performed in a raster pattern enabling easy generation of the fundus image. The data are stored in a raw digital form and analyzed after the measurement session. However, a simplified processing is performed immediately after each measurement and the OCT fundus image and selected cross-sectional images are displayed. This enables the operator to estimate whether or not the measurement is free of motion artifacts, and whether the quality of images obtained is sufficient for further processing. The preview of the acquired data can be also used for quick preliminary clinical analysis. If the data contain artifacts impeding or precluding further data processing and/or diagnosis, the measurement is repeated, and the unwanted data overwritten to save disc space. The average disk space required for one imaging session using all four protocols in a single eye is approximately 1.2 GB.

2.2 Data analysis

Fig. 2. a. Image processing procedures applied to OCT data acquired in normal retina: I. definition of the first region of interest (ROI); II. automatic generation of a smooth curve corresponding to the shape of the outer retinal contour (ORC); the order of the polynomial fit is adjusted manually; III. flattening and cropping the cross-sectional images with respect to the ORC and definition of the second ROI; IV. automatic segmentation of the entire set of threedimensional data and identification of lines representing the basal part of the RPE and the IS/OS junction. b. Contour maps representing the distance between the RPE and the outer retinal contour (RPE topography), ORC and IS/OS (IS/OS topography), and the RPE to IS/OS thickness. c. Generation of reflectivity maps: outer retina is divided into two regions (RDZ-I and RDZ-II) indicated by yellow lines. Axial summation of the RDZ-I and RDZ-II generates corresponding reflectivity maps.

Once the cross-sectional image is flattened, it is also possible to generate reflectivity maps. Such maps display the intensity distribution of light back-reflected from selected retinal layers located at specific depth ranges. The depth ranges are chosen relatively to the reference plane—the flat ORC [26

26. I. Gorczynska, V. J. Srinivasan, L. N. Vuong, R. W. Chen, J. J. Liu, E. Reichel, M. Wojtkowski, J. S. Schuman, J. S. Duker, and J. G. Fujimoto, “Projection OCT fundus imaging for visualizing outer retinal pathology in non-exudative age related macular degeneration,” Br. J. Ophthalmol. (accepted 2008, electronic version available). [PubMed]

, 27

27. B. L. Sikorski, M. Wojtkowski, J. J. Kaluzny, M. Szkulmowski, and A. Kowalczyk, “Correlation of spectral optical coherence tomography with fluorescein and indocyanine green angiography in multiple evanescent white dot syndrome,” Br. J. Ophthalmol. 92, 1552–1557 (2008). [CrossRef] [PubMed]

]. Each point of the reflectivity map is generated by summation of intensity of image pixels in the selected section of the corresponding A-scan. A fundus view is a special case of reflectivity map, in which the axial summation is performed over the entire depth of the 3-D dataset. Therefore, the fundus view displays the total intensity of the signal returning from the imaged retina. The reflectivity maps resemble confocal scanning laser ophthalmoscope (cSLO) images. However, in contrast to cSLO, OCT enables precise selection of the locations and thicknesses of the layers. In our analysis we concentrate on the outer part of the retina including photoreceptors and RPE (Fig. 2c.). We divide the outer retina into two separate depths. We refer to these depths as “retinal depth zones” (RDZ). The first retinal depth zone (RDZ-I) contains part of the outer photoreceptor segments, retinal pigment epithelium and a small part of the choroid. The second retinal depth zone (RDZ-II) contains also partially photoreceptor outer segments, photoreceptor inner segments, outer nuclear layer (Fig. 2c.). It is clear that the boundaries of retinal layers are never perfectly parallel to each other especially in eyes with pathology. However, we have selected RDZs in such way that each zone contains one highly scattering layer which dominates in the reflectivity map. In the RDZ-I, the strongest back reflection is in the RPE. In the RDZ-II the dominating signal originates from the IS/OS junction. Reflectivity maps were obtained by manual selection of the retinal depth zones. Visual estimation of chosen depths is based on one of the flattened cross-sectional image.

In this paper we also present the three-dimensional data as sets of jpeg images. Visualization is done by the OSA ISP project. Each 3-D dataset was cropped in the z-axis to minimize the volume of attached files. The data are presented in the logarithmic scale with the aspect ratio of 1:1:3 in horizontal, vertical and depth directions, respectively.

2.3 Patients and examination

SOCT imaging was performed using measurement protocols described above. Patients were asked to look straight at the internal fixation light. An appropriate scan position was achieved by the evaluation of real-time SOCT images visible in the preview mode on the monitor screen. The SOCT prototype employs alternating horizontal and vertical scans in the preview mode. This allows the operator to precisely locate the center of the macula and perform the measurement of three-dimensional data centered at the fovea.

3. Results

3.1 Normal retina

Fig. 3. Three-dimensional data acquired in a healthy eye. Left panel: macula (View 1), right panel: optic disk (View 2).

However, in some cases the fit is not perfect causing small distance variation in topographic maps. There is also noticeable presence of black dots on the RPE-IS/OS thickness map caused by irregularities of the RPE/choriocapillaris junction. These effects should be taken into consideration in further analysis. As it is expected, the reflectivity maps show almost homogenous intensity distribution in both RDZs (Fig. 2c.). In this case small variation of reflectivity can be caused by limited depth of focus of the OCT system.

3.2 Case 1. Soft drusen

In order to test the ability of tracking subtle changes in the drusen progression we demonstrate two sets of 3-D data collected in December 2005 and July 2008. These data were acquired with identical raster scanning protocol consisting of 400 horizontal and 200 vertical scans, covering 6×6mm area of the macula (Fig. 4). The measurement shown in Fig. 5 was taken 30 months after the one presented in Fig. 4. In both cases SOCT images show regular elevations of RPE with no fluid accumulation beneath the sensory retina. The RPE topography displays zones of increased distance between ORC and RPE due to sub-RPE deposits. Areas where the ORC and RPE overlay each other are coded in black. The RPE-IS/OS thickness map reveals elevations of the IS/OS junction present in close proximity to drusen. These areas have concave contours and are most likely caused by drusen elevating the neurosensory retina in their neighborhood. The IS/OS topography is a combination of the two

Fig. 4. Comparison of retinal topography mapping with reflectivity mapping in non-exudative age related macular degeneration. Soft drusen in 76 year-old patient are visualized in the crosssectional image and five SOCT maps. Full three-dimensional dataset is accessible via OSA ISP (View 3).
Fig. 5. Results of a follow up (30 months) imaging of the 76 year-old patient with soft drusen. Drusen growth can be assessed by comparison of OCT maps with the corresponding maps in Fig. 4. Full three-dimensional dataset is accessible via OSA ISP (View 4).

This generates bright spots in RDZ-II and corresponding dark patches in RDZ-I. The pattern of dark areas in the RDZ-I matches exactly the pattern of bright regions in the RDZ-II. This indicates that no atrophy is present in the elevated RPE.

The thickness maps as well as the reflectivity maps show progression in drusen growth. The former can measure the progress quantitatively, while the later can give only qualitative information. However, the reflectivity maps provide information about the condition of RPE in the sense that they can visualize pigmentary changes in this layer.

3.3 Case 2. Confluent drusen

Figure 6 shows three-dimensional data and their analysis in the case of soft confluent drusen in AMD. 61-years-old patient with choroidal neovascularization in the right eye complained of decrease in contrast sensitivity with 20/20 visual acuity in the left eye. Fluorescence angiography revealed soft confluent drusen clustering around the fovea. SOCT showed regular elevations of RPE without fluid under the sensory retina. The RPE topography shows regular, oval elevations corresponding to confluent drusen surrounding the fovea. The contours of drusen are also clearly visible in the reflectivity maps.

One year later, visual acuity remained unchanged but fluorescence angiography demonstrated an increase in drusen size. SOCT confirmed the diagnosis of soft drusen with no sign of choroidal neovascularization (Fig 7). The process of drusen growth is clearly visible in both RPE topography and IS/OS topography, as well as in both reflectivity maps. In addition, the reflectivity maps do not indicate any pigmentary changes in the RPE. The drusen grew approximately 30µm in axial dimension and could be measured in both RPE topography and IS/OS topography. High contrast in both the RPE topography and in the RDZ-I reflectivity map enables to compare accuracies of lesion reconstructions. In both maps the shapes of drusen edges are very similar. This indicates that both methods should have approximately the same accuracy in delineation of soft drusen.

Fig. 6. Comparison of retinal topography mapping with reflectivity mapping: confluent drusen, 61 year-old patient. Full three-dimensional dataset is accessible via OSA ISP (View 5).
Fig. 7. Results of a follow up (12 months) imaging of the 61 year-old patient with confluent drusen. Full three-dimensional dataset is accessible via OSA ISP (View 6).

3.4 Case 3. Choroidal neovascularization (CNV)

Fig. 8. Comparison of retinal topography mapping with reflectivity mapping: choroidal neovascularisation in age related macular degeneration, 66 year-old patient. Full three-dimensional dataset is accessible via OSA ISP (View 7).

Fig. 9. Results of a follow up (22 months) imaging of the 66 year-old patient with choroidal neovascularisation in age related macular degeneration. Full three-dimensional dataset is accessible via OSA ISP (View 8).

3.5 Case 4. Elevations of neurosensory retina in chronic central serous chorioretinopathy (CSC)

A case of the neurosensory retinal detachment in central serous chorioretinopathy (CSCR) is demonstrated in Fig. 10. A 43-year-old man was presented with CSCR with decreased visual acuity in the left eye sustaining over 3 years. Fundus autofluorescence image demonstrated a large area of RPE damage due to chronic subretinal fluid accumulation. SOCT imaging revealed shallow elevation of RPE, as well as secondary degenerative changes in RPE.

Contour maps revealed a small deposit in RPE, which creates a small oval hill on the RPE topography. The same structure is also well visible in IS/OS topography and RDZ-II reflectivity map. Dramatic loss of reflectivity in the IS/OS junction within elevated areas of the retina generates an artificial depression in RPE - IS/OS thickness map and IS/OS topography. In such circumstances, the segmentation algorithm selects the brightest layer above the posterior boundary of RPE, which in this case is the anterior boundary of RPE. As a result, the blue area corresponds to the RPE layer thickness. This area visible in the RPE-IS/OS thickness map indicates indirectly the region of the retinal elevation. This case demonstrates that under specific conditions, quantification loss of the method presented, in the meaning of thickness or topography analysis, is quite possible. However, these unwanted effects can be used to estimate the lateral spread of elevated retina. RDZ-I reflectivity map shows almost homogenous distribution of back-reflected light. Only small black dots indicate the presence of pathological changes in RPE. The biggest irregular one corresponds to the deposit whereas multiple small dots correspond to very focal hyperreflective spots in RDZ-II and may indicate the presence of small highly reflective or non-transparent deposits or pigment clumping. These findings are not revealed in the contour maps. The RDZ-II reflectivity map visualizes only partially the region of detachment.

Fig. 10. Comparison of retinal topography mapping with reflectivity mapping: elevations of neurosensory retina in the chronic central serous chorioretinopathy, 43 year-old patient. Full three-dimensional dataset is accessible via OSA ISP (View 9).

The black field corresponds only to that part of the detached tissue, which was elevated higher than the outer plexiform layer level. Therefore, it does not allow to determinate exactly the region of detached retina. In contrast, the RPE-IS/OS thickness map and IS/OS topography both provide information about the border of the detached retina, which correlates well with the autofluorescence image.

3.6 Case 5. Rhegmatogenous retinal detachment

A 17-year-old patient complained of veil obstructing naso-inferior portion of the visual field in the left eye. Her visual acuity was 20/200. The patient was diagnosed with retinal detachment. A red free fundus photograph and direct ophthalmoscopic fundus examination showed an elevation of peripheral retina, which also involved the temporal part of the fovea. SOCT cross-sectional images of the macula enabled precise assessment of the magnitude of detachment (Fig. 11). The imaging revealed small cystic changes in inner retina and disorganization of photoreceptors. It is not clear whether the brighter part of RPE in the central fovea corresponds to secondary degenerative changes or is only caused by decreased scattering. The same effect is visible in the RDZ-I reflectivity map as an irregular bright patch in the central part of the map. This effect is also visible in contour maps as the artificial depression (blue region) indicating strong decrease of the reflectivity of detached IS/OS in the foveal region.

Both IS/OS topography and RPE-IS/OS thickness map clearly pinpoint the region of detachment and allow to determine magnitude and area.

Fig. 11. Comparison of retinal topography mapping with reflectivity mapping: elevations of neurosensory retina in retinal detachment, 17 year-old patient. Full three-dimensional dataset is accessible via OSA ISP (View 10).

4. Conclusions

We have observed that different types of RPE elevations and neurosensory retina detachments produce specific patterns visible in the retinal topography and reflectivity maps. Comparison of our data with standard diagnostics shows that the ORC-RPE map provides adequate information about the distribution of the RPE detachments over the entire measured region. RPE-IS/OS thickness maps demonstrate the distance between RPE and IS/OS junction and can indicate even small deviations from the normal shape of those layers. These maps reveal elevation of the IS/OS junction caused by a small amount of both subretinal fluid and drusen. All elevations of the IS/OS junction with the reference to ORC can be observed in IS/OS topography. This map enables evaluation of RPE elevations with respect to areas of the neurosensory retina detachment and therefore serves as a consistency test between the RPE topography and IS/OS-RPE thickness map.

The topography and thickness maps can measure the sizes and volumes of outer retinal elevations and quantitatively assess their changes between consecutive examinations. However, the material under the elevation is not always visible in these maps. Therefore, additional information is needed to unequivocally estimate the origin of the elevations. This information can be obtained either form cross-sectional images or from reflectivity maps. The RPE detachments due to drusen are visible as dark areas in the RDZ-I with corresponding bright regions in the RDZ-II. The neurosensory retina detachments, resulting from accumulation of highly transparent fluid, are projected in the RDZ-I as areas of slightly decreased brightness. However, the strong signal from intact RPE still dominates in this depth zone. RDZ-II visualizes this type of detachment as a hyporeflective region. The advantage of the reflectivity maps is also in their capability of visualizing changes in light scattering within selected retinal layers. For example, they can reveal pigmentary changes in the RPE and therefore may provide information important in estimating the development of pathologies such as AMD.

More advanced signal analysis or more sophisticated SOCT techniques, like polarization sensitive detection [31–35

31. 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, 22–24 (2008). [CrossRef]

] or flow measurements [36

36. R. A. Leitgeb, L. Schmetterer, W. Drexler, A. F. Fercher, R. J. Zawadzki, and T. Bajraszewski, “Real-time assessment of retinal blood flow with ultrafast acquisition by color Doppler Fourier domain optical coherence tomography,” Opt. Express 11, 3116–3121 (2003). [CrossRef] [PubMed]

], would probably help to differentiate morphological components in a more detailed way. Potentially, this could lead to definition of more specific markers of the disease progression. Unfortunately, these methods are much more time consuming and more challenging to implement than the time-effective segmentation procedure demonstrated in this paper.

In the presented results we show that reflectivity maps and topography maps can provide unique and complementary information about the condition of retina. Combined information revealed by both data processing methods may be helpful in correct assessment of the disease. Moreover, both ways of displaying the three-dimensional data can serve as a convenient and time-effective method of reading large OCT datasets and evaluating disease progression or results of treatment in clinical practice. The topography maps can measure this progress quantitatively, while reflectivity maps give qualitative information about light scattering changes within specific retinal layers. Analysis of both types of maps, in correlation with OCT cross-sectional images and results of standard ophthalmic testing, provides additional knowledge which may be used in comprehensive assessment of retinal pathologies, their development and pathogenesis.

Three-dimensional OCT datasets presented in this study can be used in the future for further development of OCT processing tools. Particularly, multiple measurements of the same disease in long term can be helpful in evaluation of new algorithms and data visualization methods.

Acknowledgments

This work was supported by EURYI grant/award funded by the European Heads of Research Councils (EuroHORCs) and the European Science Foundation (ESF) and Polish Ministry of Science and Higher Education, grants for 2006 to 2008. Maciej Wojtkowski acknowledges additional support from the Foundation for Polish Science (Homing project and EURYI) and Rector of NCU for the scientific grant 504-F. Maciej Szkulmowski acknowledges support from the Polish Ministry of Science, grants for 2005 to 2008. J.G. Fujimoto receives royalties from intellectual property licensed from M.I.T. to Carl Zeiss Meditec.

References and links

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M. Wojtkowski, R. Leitgeb, A. Kowalczyk, T. Bajraszewski, and A. F. Fercher, “In vivo human retinal imaging by Fourier domain optical coherence tomography,” J. Biomed. Opt. 7, 457–463 (2002). [CrossRef] [PubMed]

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M. Wojtkowski, V. J. Srinivasan, T. H. Ko, J. G. Fujimoto, A. Kowalczyk, and J. S. Duker, “Ultrahighresolution high-speed Fourier domain optical coherence tomography and methods for dispersion compensation,” Opt. Express 12, 2404–2422 (2004). [CrossRef] [PubMed]

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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, 2054–2065 (2006). [CrossRef] [PubMed]

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M. Wojtkowski, V. Srinivasan, J. G. Fujimoto, T. Ko, J. S. Schuman, A. Kowalczyk, and J. S. Duker, “Three-dimensional retinal imaging with high-speed ultrahigh-resolution optical coherence tomography,” Ophthalmology 112, 1734–1746 (2005). [CrossRef] [PubMed]

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S. L. Jiao, R. Knighton, X. R. Huang, G. Gregori, and C. A. Puliafito, “Simultaneous acquisition of sectional and fundus ophthalmic images with spectral-domain optical coherence tomography,” Opt. Express 13, 444–452 (2005). [CrossRef] [PubMed]

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R. A. Leitgeb, W. Drexler, A. Unterhuber, B. Hermann, T. Bajraszewski, T. Le, A. Stingl, and A. F. Fercher, “Ultrahigh resolution Fourier domain optical coherence tomography,” Opt. Express 12, 2156–2165 (2004). [CrossRef] [PubMed]

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B. Cense, N. A. Nassif, T. C. Chen, M. C. Pierce, S.-H. 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]

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T. H. Ko, J. G. Fujimoto, J. S. Schuman, L. A. Paunescu, A. M. Kowalevicz, I. Hartl, W. Drexler, G. Wollstein, H. Ishikawa, and J. S. Duker, “Comparison of ultrahigh- and standard-resolution optical coherence tomography for imaging macular pathology,” Ophthalmology 112, 1922 (2005). [CrossRef] [PubMed]

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11.

T. H. Ko, J. G. Fujimoto, J. S. Duker, L. A. Paunescu, W. Drexler, C. R. Baumal, C. A. Puliafito, E. Reichel, A. H. Rogers, and J. S. Schuman, “Comparison of ultrahigh- and standard-resolution optical coherence tomography for imaging macular hole pathology and repair,” Ophthalmology 111, 2033–2043 (2004). [CrossRef] [PubMed]

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M. G. Wirtitsch, E. Ergun, B. Hermann, A. Unterhuber, M. Stur, C. Scholda, H. Sattmann, T. H. Ko, J. G. Fujimoto, and W. Drexler, “Ultrahigh resolution optical coherence tomography in macular dystrophy,” Am. J. Ophthalmol. 140, 976–983 (2005). [CrossRef] [PubMed]

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U. M. Schmidt-Erfurth and C. Pruente, “Management of neovascular age-related macular degeneration,” Prog. Retin Eye Res. 26, 437–451 (2007). [CrossRef] [PubMed]

14.

C. Ahlers, W. Geitzenauer, C. Simader, G. Stock, I. Golbaz, K. Polak, M. Georgopoulo, and U. Schmidt-Erfurth, “New perspectives in diagnostics. High-resolution optical coherence tomography for age-related macular degeneration,” Ophthalmologe 105, 248–254 (2008). [CrossRef]

15.

C. Scholda, M. Wirtitsch, B. Hermann, A. Unterhuber, E. Ergun, H. Sattmann, T. H. Ko, J. G. Fujimoto, A. F. Fercher, M. Stur, U. Schmidt-Erfurth, and W. Drexler, “Ultrahigh resolution optical coherence tomography of macular holes,” Retina 26, 1034–1041 (2006). [CrossRef] [PubMed]

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E. M. Anger, A. Unterhuber, B. Hermann, H. Sattmann, C. Schubert, J. E. Morgan, A. Cowey, P. K. Ahnelt, and W. Drexler, “Ultrahigh resolution optical coherence tomography of the monkey fovea. Identification of retinal sublayers by correlation with semithin histology sections,” Exp. Eye Res. 78, 1117–1125 (2004). [CrossRef] [PubMed]

17.

W. Drexler, H. Sattmann, B. Hermann, T. H. Ko, M. Stur, A. Unterhuber, C. Scholda, O. Findl, M. Wirtitsch, J. G. Fujimoto, and A. F. Fercher, “Enhanced visualization of macular pathology with the use of ultrahigh-resolution optical coherence tomography,” Arch. Ophthalmol. 121, 695–706 (2003). [CrossRef] [PubMed]

18.

V. J. Srinivasan, B. K. Monson, M. Wojtkowski, R. A. Bilonick, I. Gorczynska, R. Chen, J. S. Duker, J. S. Schuman, and J. G. Fujimoto, “Characterization of outer retinal morphology with high-speed, ultrahighresolution optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 49, 1571–1579 (2008). [CrossRef] [PubMed]

19.

M. Szkulmowski, M. Wojtkowski, B. Sikorski, T. Bajraszewski, V. J. Srinivasan, A. Szkulmowska, J. J. Kaluzny, J. G. Fujimoto, and A. Kowalczyk, “Analysis of posterior retinal layers in spectral optical coherence tomography images of the normal retina and retinal pathologies,” J. Biomed. Opt. 12, 041207 (2007). [CrossRef] [PubMed]

20.

A. G. Podoleanu, M. Seeger, G. M. Dobre, D. J. Webb, D. A. Jackson, and F. W. Fitzke, “Transversal and longitudinal images from the retina of the living eye using low coherence reflectometry,” J. Biomed. Opt. 3, 12–20 (1998). [CrossRef]

21.

A. G. Podoleanu, J. A. Rogers, D. A. Jackson, and S. Dunne, “Three dimensional OCT images from retina and skin,” Opt. Express 7, 292–298 (2000). [CrossRef] [PubMed]

22.

C. K. Hitzenberger, P. Trost, P. W. Lo, and Q. Y. Zhou, “Three-dimensional imaging of the human retina by high-speed optical coherence tomography,” Opt. Express 11, 2753–2761 (2003). [CrossRef] [PubMed]

23.

A. G. Podoleanu and D. A. Jackson, “Combined optical coherence tomograph and scanning laser ophthalmoscope,” Electron. Lett. 34, 1088–1090 (1998). [CrossRef]

24.

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

25.

A. G. Podoleanu, G. M. Dobre, R. G. Cucu, R. Rosen, P. Garcia, J. Nieto, D. Will, R. Gentile, T. Muldoon, J. Walsh, L. A. Yannuzzi, Y. Fisher, D. Orlock, R. Weitz, J. A. Rogers, S. Dunne, and A. Boxer, “Combined multiplanar optical coherence tomography and confocal scanning ophthalmoscopy,” J. Biomed. Opt. 9, 86–93 (2004). [CrossRef] [PubMed]

26.

I. Gorczynska, V. J. Srinivasan, L. N. Vuong, R. W. Chen, J. J. Liu, E. Reichel, M. Wojtkowski, J. S. Schuman, J. S. Duker, and J. G. Fujimoto, “Projection OCT fundus imaging for visualizing outer retinal pathology in non-exudative age related macular degeneration,” Br. J. Ophthalmol. (accepted 2008, electronic version available). [PubMed]

27.

B. L. Sikorski, M. Wojtkowski, J. J. Kaluzny, M. Szkulmowski, and A. Kowalczyk, “Correlation of spectral optical coherence tomography with fluorescein and indocyanine green angiography in multiple evanescent white dot syndrome,” Br. J. Ophthalmol. 92, 1552–1557 (2008). [CrossRef] [PubMed]

28.

J. J. Kaluzny, M. Wojtkowski, B. L. Sikorski, M. Szkulmowski, A. Szkulmowska, T. Bajraszewski, J. G. Fujimoto, J. S. Duker, J. S. Schuman, and A. Kowalczyk, “Analysis of the outer retina reconstructed by high-resolution, three-dimensional spectral domain optical coherence tomography,” Ophthalmic Surg. Lasers Imaging 39, S30–S36 (2008).

29.

J. C. Russ, The Image Processing Handbook (CRC Press, 2002).

30.

A. R. Weeks, The Fundamentals of Electronic Image Processing, (SPIE Press & IEEE Press, 1996).

31.

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, 22–24 (2008). [CrossRef]

32.

S. Michels, M. Pircher, W. Geitzenauer, C. Simader, E. Gotzinger, O. Findl, U. Schmidt-Erfurth, and C. K. Hitzenberger, “Value of polarisation-sensitive optical coherence tomography in diseases affecting the retinal pigment epithelium,” Br. J. Ophthalmol. 92, 204–209 (2008). [CrossRef] [PubMed]

33.

Y. Yasuno, S. Makita, Y. Sutoh, M. Itoh, and T. Yatagai, “Birefringence imaging of human skin by polarization-sensitive spectral interferometric optical coherence tomography,” Opt. Lett. 27, 1803–1805 (2002). [CrossRef]

34.

Y. Yasuno, S. Makita, T. Endo, M. Itoh, T. Yatagai, M. Takahashi, C. Katada, and M. Mutoh, “Polarization-sensitive complex Fourier domain optical coherence tomography for Jones matrix imaging of biological samples,” Appl. Phys. Lett. 85, 3023–3025 (2004). [CrossRef]

35.

M. C. Pierce, J. Strasswimmer, B. H. Park, B. Cense, and J. F. de Boer, “Birefringence measurements in human skin using polarization-sensitive optical coherence tomography,” J. Biomed. Opt. 9, 287–291 (2004). [CrossRef] [PubMed]

36.

R. A. Leitgeb, L. Schmetterer, W. Drexler, A. F. Fercher, R. J. Zawadzki, and T. Bajraszewski, “Real-time assessment of retinal blood flow with ultrafast acquisition by color Doppler Fourier domain optical coherence tomography,” Opt. Express 11, 3116–3121 (2003). [CrossRef] [PubMed]

OCIS Codes
(100.2000) Image processing : Digital image processing
(170.1610) Medical optics and biotechnology : Clinical applications
(170.1650) Medical optics and biotechnology : Coherence imaging
(170.4470) Medical optics and biotechnology : Ophthalmology
(170.4500) Medical optics and biotechnology : Optical coherence tomography

ToC Category:
Visualization and Image Processing in OCT

History
Original Manuscript: July 28, 2008
Revised Manuscript: January 21, 2009
Manuscript Accepted: January 23, 2009
Published: March 2, 2009

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

Citation
Maciej Wojtkowski, Bartosz L. Sikorski, Iwona Gorczynska, Michalina Gora, Maciej Szkulmowski, Danuta Bukowska, Jakub Kaluzny, James G. Fujimoto, and Andrzej Kowalczyk, "Comparison of reflectivity maps and outer retinal topography in retinal disease by 3-D Fourier domain optical coherence tomography," Opt. Express 17, 4189-4207 (2009)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=oe-17-5-4189


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References

  1. D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, "Optical coherence tomography," Science 254, 1178-1181 (1991). [CrossRef] [PubMed]
  2. M. Wojtkowski, R. Leitgeb, A. Kowalczyk, T. Bajraszewski, and A. F. Fercher, "In vivo human retinal imaging by Fourier domain optical coherence tomography," J. Biomed. Opt. 7, 457-463 (2002). [CrossRef] [PubMed]
  3. M. Wojtkowski, V. J. Srinivasan, T. H. Ko, J. G. Fujimoto, A. Kowalczyk, and J. S. Duker, "Ultrahigh-resolution high-speed Fourier domain optical coherence tomography and methods for dispersion compensation," Opt. Express 12, 2404-2422 (2004). [CrossRef] [PubMed]
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  5. M. Wojtkowski, V. Srinivasan, J. G. Fujimoto, T. Ko, J. S. Schuman, A. Kowalczyk, and J. S. Duker, "Three-dimensional retinal imaging with high-speed ultrahigh-resolution optical coherence tomography," Ophthalmology 112, 1734-1746 (2005). [CrossRef] [PubMed]
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  7. R. A. Leitgeb, W. Drexler, A. Unterhuber, B. Hermann, T. Bajraszewski, T. Le, A. Stingl, and A. F. Fercher, "Ultrahigh resolution Fourier domain optical coherence tomography," Opt. Express 12, 2156-2165 (2004). [CrossRef] [PubMed]
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  11. T. H. Ko, J. G. Fujimoto, J. S. Duker, L. A. Paunescu, W. Drexler, C. R. Baumal, C. A. Puliafito, E. Reichel, A. H. Rogers, and J. S. Schuman, "Comparison of ultrahigh- and standard-resolution optical coherence tomography for imaging macular hole pathology and repair," Ophthalmology 111, 2033-2043 (2004). [CrossRef] [PubMed]
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  13. U. M. Schmidt-Erfurth and C. Pruente, "Management of neovascular age-related macular degeneration," Prog. Retin Eye Res. 26, 437-451 (2007). [CrossRef] [PubMed]
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  15. C. Scholda, M. Wirtitsch, B. Hermann, A. Unterhuber, E. Ergun, H. Sattmann, T. H. Ko, J. G. Fujimoto, A. F. Fercher, M. Stur, U. Schmidt-Erfurth, and W. Drexler, "Ultrahigh resolution optical coherence tomography of macular holes," Retina 26, 1034-1041 (2006). [CrossRef] [PubMed]
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  19. M. Szkulmowski, M. Wojtkowski, B. Sikorski, T. Bajraszewski, V. J. Srinivasan, A. Szkulmowska, J. J. Kaluzny, J. G. Fujimoto, and A. Kowalczyk, "Analysis of posterior retinal layers in spectral optical coherence tomography images of the normal retina and retinal pathologies," J. Biomed. Opt. 12, 041207 (2007). [CrossRef] [PubMed]
  20. A. G. Podoleanu, M. Seeger, G. M. Dobre, D. J. Webb, D. A. Jackson, and F. W. Fitzke, "Transversal and longitudinal images from the retina of the living eye using low coherence reflectometry," J. Biomed. Opt. 3, 12-20 (1998). [CrossRef]
  21. A. G. Podoleanu, J. A. Rogers, D. A. Jackson, and S. Dunne, "Three dimensional OCT images from retina and skin," Opt. Express 7, 292-298 (2000). [CrossRef] [PubMed]
  22. C. K. Hitzenberger, P. Trost, P. W. Lo, and Q. Y. Zhou, "Three-dimensional imaging of the human retina by high-speed optical coherence tomography," Opt. Express 11, 2753-2761 (2003). [CrossRef] [PubMed]
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  24. M. Pircher, E. Gotzinger, and C. K. Hitzenberger, "Dynamic focus in optical coherence tomography for retinal imaging," J. Biomed. Opt. 11, 054013 (2006). [CrossRef] [PubMed]
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  26. I. Gorczynska, V. J. Srinivasan, L. N. Vuong, R. W. Chen, J. J. Liu, E. Reichel, M. Wojtkowski, J. S. Schuman, J. S. Duker, and J. G. Fujimoto, "Projection OCT fundus imaging for visualizing outer retinal pathology in non-exudative age related macular degeneration," Br. J. Ophthalmol.(accepted2008, electronic version available). [PubMed]
  27. B. L. Sikorski, M. Wojtkowski, J. J. Kaluzny, M. Szkulmowski, and A. Kowalczyk, "Correlation of spectral optical coherence tomography with fluorescein and indocyanine green angiography in multiple evanescent white dot syndrome," Br. J. Ophthalmol. 92, 1552-1557 (2008). [CrossRef] [PubMed]
  28. J. J. Kaluzny, M. Wojtkowski, B. L. Sikorski, M. Szkulmowski, A. Szkulmowska, T. Bajraszewski, J. G. Fujimoto, J. S. Duker, J. S. Schuman, and A. Kowalczyk, "Analysis of the outer retina reconstructed by high-resolution, three-dimensional spectral domain optical coherence tomography," Ophthalmic Surg. Lasers Imaging 39, S30-S36 (2008).
  29. J. C. Russ, The Image Processing Handbook (CRC Press, 2002).
  30. A. R. Weeks, The Fundamentals of Electronic Image Processing, (SPIE Press and IEEE Press, 1996).
  31. 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, 22-24 (2008). [CrossRef]
  32. S. Michels, M. Pircher, W. Geitzenauer, C. Simader, E. Gotzinger, O. Findl, U. Schmidt-Erfurth, and C. K. Hitzenberger, "Value of polarisation-sensitive optical coherence tomography in diseases affecting the retinal pigment epithelium," Br. J. Ophthalmol. 92, 204-209 (2008). [CrossRef] [PubMed]
  33. Y. Yasuno, S. Makita, Y. Sutoh, M. Itoh, and T. Yatagai, "Birefringence imaging of human skin by polarization-sensitive spectral interferometric optical coherence tomography," Opt. Lett. 27, 1803-1805 (2002). [CrossRef]
  34. Y. Yasuno, S. Makita, T. Endo, M. Itoh, T. Yatagai, M. Takahashi, C. Katada, and M. Mutoh, "Polarization-sensitive complex Fourier domain optical coherence tomography for Jones matrix imaging of biological samples," Appl. Phys. Lett. 85, 3023-3025 (2004). [CrossRef]
  35. M. C. Pierce, J. Strasswimmer, B. H. Park, B. Cense, and J. F. de Boer, "Birefringence measurements in human skin using polarization-sensitive optical coherence tomography," J. Biomed. Opt. 9, 287-291 (2004). [CrossRef] [PubMed]
  36. R. A. Leitgeb, L. Schmetterer, W. Drexler, A. F. Fercher, R. J. Zawadzki, and T. Bajraszewski, "Real-time assessment of retinal blood flow with ultrafast acquisition by color Doppler Fourier domain optical coherence tomography," Opt. Express 11, 3116-3121 (2003). [CrossRef] [PubMed]

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