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High-Resolution, in Vivo Imaging of the Human Cone Photoreceptor Mosaic

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High-Resolution, in Vivo Imaging of the Human Cone Photoreceptor Mosaic High-resolution, in vivo imaging of the human cone photoreceptor mosaic Alex R. Wade, B.A. A thesis submitted for the degree of Doctor of Philosophy at University College London, U.K. Institute of Ophthalmology University College London November 1998 ProQuest Number: 10015876 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. uest. ProQuest 10015876 Published by ProQuest LLC(2016). Copyright of the Dissertation is held by the Author. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code. Microform Edition © ProQuest LLC. ProQuest LLC 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, Ml 48106-1346 Abstract This thesis describes a project to image the human retina in vivo using a modified confocal laser scanning ophthalmoscope (cLSO). An optical attachment to an existing prototype cLSO was designed and constructed. The attachment reduced the field of view of the cLSO to approximately three degrees of visual angle at the retina but also reduced the amount of light returning to the imaging detector and consequently lowered the signal to noise ratio. The video output of the cLSO was digitised using a high-speed, low-noise video frame grabber. Many individual frames from a single imaging sequence were aligned and averaged using novel image processing software to improve the signal to noise ratio. Arrays of point-like structures could then be identified in the final, processed images. Experiments were undertaken to confirm the point structures corresponded to cone photoreceptor apertures. • The point sizes and spaeings were compatible with those found in anatomical studies and it was shown that point spacing increased with increasing retinal eccentricity - a fact which was also predicted from anatomical studies. • By fitting an additional, high-intensity fixation target to the cLSO it was shown that the point structures were located at the focal plane at which light is trapped into the visual system. The above results were evidence that the point sources were produced by light reflecting from the cone photoreceptor apertures: the LSO/MSA combination was imaging the cone mosaic. An additional experiment was conducted to study the time course of reflectivity changes in individual photoreceptors. It was shown that at least one factor contributing to the variation in imaged photoreceptor brightness was a signal correlated to the arterial pulse. This project has shown that it is possible to routinely image the cone photoreceptor mosaic in vivo at retinal eccentricities of between two and four degrees using a cLSO. It is also possible to use this device to obtain physiological imaging data from the cone mosaic with a temporal resolution of 1/25 second. Declaration I declare that this thesis submitted for the degree of PhD is my own composition and the data presented herein is my own original work, unless otherwise stated. Alex R. Wade, B.A. Acknowledgements I have been fortunate to have conducted this PhD in a well-equipped lab under the excellent supervision of Prof. Fred Fitzke. It has also been pleasure to work with other members of the department of Visual Science: Dr. Glen Jeffery has provided valuable advice on retinal anatomy and supplied the biological samples used in chapter 4. Adrian Williams, Tony Halfyard, Roger Chan and Chris Jubb have provided both technical support and constant encouragement. The prototype cLSO was donated by Carl Zeiss GmbH who also made technical information and full ZEMAX models of the device available. The technical staff at Matrox Electronic Imaging also provided details of their pattern-matching software routine and valuable hardware support. The lab is funded by Marks and Spencer, Fight for Sight and the Foundation Fighting Blindness along with the MRC who also supported my PhD. Dr. Michael Scholz of the Technische Universitat in Berlin was kind enough to devote computer time to perform blind deconvolution on some of my images and Dr. Austin Roorda gave permission to use the unpublished image in figure 1.10. I would like to thank my many excellent teachers throughout the years: John Biffin and Dr. Andrea Brand for communicating the excitement of biological science. Prof. John Mollon who guided me onto the one true path of vision research and Dr. Rhodri Cusack who has made learning an adventure for many years. Finally, I must thank my family for their unwavering support over the years and Isabel for proof-reading this thesis and helping me to maintain my focus. Table of contents ABSTRACT 2 DECLARATION 4 ACKNOWLEDGEMENTS 5 TABLE OF CONTENTS 6 LIST OF FIGURES 10 ABBREVIATIONS, SYMBOLS AND ACRONYMS 13 PUBLICATIONS 15 CHAPTER 1 - INTRODUCTION 16 Overview of PhD - description of aims and accomplishments. 17 Overview of photoreceptor imaging: 19 Background 19 Physiological optics 21 The model eye 21 The pupil and the MTF 22 Wavefront aberration 26 Photoreceptor biology 27 Photoreceptor types 31 Waveguide properties 36 Spacing and mosaic 41 High-resolution in vivo retinal imaging 45 Ocular speckle interferometry 48 Adaptive optics 49 The confocal LSO 51 Image processing 58 Summary 61 FIGURE 1.10 62 CHAPTER 2 - METHODS AND MATERIALS 63 Hardware 63 Zeiss confocal LSO 63 Beam profile and power 67 Micro scanning attachment (MSA) 68 Fixation and stabilisation 68 Pupil dilation 69 Image acquisition 69 Software 70 Image averaging 70 CHAPTER 3 - IMAGE ALIGNMENT 72 Noise and the SNR 72 Normalised cross-correlation 78 Fourier domain convolution 79 Hierarchical resolution search 80 MIL pattern matching routine 81 Low-pass filtering 82 Estimates of image signal to noise ratios 88 Signal-dependent noise 90 Averaged images 93 Test target 96 Autofluorescence images 96 High-magnification images 97 Discussion 99 CHAPTER 4 - PRELIMINARY STUDIES 101 Optics design - optimisation and modelling in ZEMAX 101 Results 105 Variation in detected power 105 Axial resolution 108 Lateral resolution 110 Scan geometry 116 Biological samples 116 Ferret retina 118 Post-mortem human retina 119 7n Vi VO human retinal imaging 121 Discussion 127 CHAPTER 5 - PHOTORECEPTOR IMAGING 129 Introduction 129 Mosaic spacing 129 Mosaic focal plane 134 Results 136 Images and montages 136 Cone spacing 140 Image focal plane 145 Discussion 154 CHAPTER 6 - CONE REFLECTIVITY CHANGES OVER TIME 159 Introduction 159 Analysis methods 164 Image acquisition 164 Image signal analysis 167 Results 169 Discussion 177 CHAPTER 7 - CONCLUSIONS 179 APPENDIX A 182 COMPARISON OF CONVENTIONAL AND CONFOCAL IMAGING SYSTEMS 182 Single lens imaging system image formation 182 Confocal scanning imaging system 185 The MTF 189 REFERENCES 192 List of figures FIGURE Descriotion 1.1 Cross section of eye 1.2 MTFs of two model eyes 1.3 Diagrams of photoreceptors 1.4 Rod density map 1.5 Cone density map 1.6 The Stiles-Crawford effect 1.7 Cone packing - spacing and density 1.8 Speckle interferometry 1.9 Confocal microscope 1.10 Example of blind deconvolution 2.1 Zeiss confocal LSO 2.2 Beam expansion by the MSA 3.1 Example of image averaging 3.2 Adding noise to a test image 3.3 2-dimensional cross-correlation 3.4 Filtered cross-correlation 3.5 Mean errors in peak location 3.6 Raw image frames 3.7 Autofluorescence - variance against intensity. 3.8 High-magnification - variance against intensity 3.9 Decrease in image variance - test target 3.10 Decrease in image variance - AF image 3.11 Decrease in image variance - high magnification 3.12 Fourier domain filtering 4.1 MSA point spread functions 4.2 Scan angle point spread functions 4.3 Fourier analysis of power variation 10 4.4 Axial response 4.5 SEM image of pinhole 4.6 LSO images of pinhole 4.7 Response to a 5 micron line 4.8 Images of calibrated graticule 4.9 Images of post-mortem ferret retina 4.10 Images of post-mortem human retina 4.11 in vivo retinal image with MSA 4.12 Locating high-magnification images 4.13 High magnification images from 8 subjects 5.1 Yellott’s ring 5.2 Irregularities in the cLSO scan 5.3 High-resolution images taken with the LSO/MSA 5.4a Montage of high magnification images from subject AW 5.4b Montage of high-magnification images from subject RC 5.5 Images from 3 retinal locations 5.6 Array spacing at 3 locations 5.7 Power spectra - real data and simulations 5.8 Diagram of fixation target system 5.9 Shift in retinal focal plane with target position 5.10 Raw high magnification images from different focal planes 5.11 Use of Fourier transforms to find low-frequency details 5.12 Plot of image power against retinal focal plane 5.13 Comparison with images from (Miller, Williams et al. 1996) 5.14 Comparison with AO system 6.1 Change in photoreceptor array appearance over time 6.2 Example of cross-correlation peak heights 6.3 Signal detection 6.4 Cross-correlation matrix for blank target 6.5 Cross-correlation matrix for resting retina 11 6.6 Fourier analysis of cross-correlation data 6.7 Fourier analysis of raw intensity data A1 Schematic imaging system A2 Schematic confocal imaging system A3 Comparison of conventional and confocal PSFs A4 Optical sectioning power of conventional and confocal systems 12 Abbreviations, symbols and acronyms X Wavelength of imaging light AF Auto-fluorescence AO Adaptive optics bpm Beats per minute cGMP Cyclic guanosine mono phosphate cLSO Confocal LSO cpd Cycles per
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