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Improved Image Quality in AO-OCT through System Characterization

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Presentation on theme: "Improved Image Quality in AO-OCT through System Characterization"— Presentation transcript:

1 Improved Image Quality in AO-OCT through System Characterization
Samelia O. Okpodu Vision Science and Adanced Retinal Imaging Laboratory, Department of Ophthalmology & Vision Science, University of California, Davis Mentor: Dr. Julia W. Evans Faculty Advisor: Dr. John S. Werner Additional Collaborators: Dr. Robert J. Zawadzki, Steve Jones, Dr. Scot S. Olivier Home Institution: Norfolk State University

2 Outline Background Data Importance Proof of Principle AO-OCT vs. OCT
My Research Installation Process Data Proof of Principle Conclusion &Future Directions

3 Background-What is OCT?
Optical Coherence Tomography (OCT) In vivo imaging technique Diagnosis and monitoring treatment of human retinal diseases OCT permits us to see retinal layers In Vivo imaging technique that sends out femtosecond infrared pulses and uses optical interference to sense reflections from tissue inhomogenities. OCT- you can see contrast b/w the layers which is caused by back reflection. Where the lines appear lighter you’re seeing more back reflection. OCT B-Scan. UCD

4 OCT vs. AO-OCT OCT Allows rapid acquisition of cross sectional retinal images. Volumetric reconstruction of retinal structures with micrometer axial resolution. AO-OCT Improves lateral resolution. 3 microns in all directions. --AO-OCT scan, AO allows us to have improved lateral resolution AO-OCT Reconstruction. UCD

5 UCD AO-OCT System Far-Field CCD S-H WFS In an OCT system Calibration errors limit the image quality A large part of system characterization is understanding calibration error WFS provides relative measurements of WF error based on calibration Far Field camera gives us a way to measure calibration independently of the WFS

6 My Research Installing a Far-Field Camera
Proof of principle testing (basic system testing) Measured errors which affect OCT image quality Used wavefront measurements to simulate the PSF Used the far field camera to measure the PSF Calibration errors: errors that are not seen by the wavefront sensor

7 Installation Process Proper components Optical Constraints
Machine Shop Optical Constraints Far Field and WFS both require pupil planes Mechanical/ Space Constraints Mechanical/ Space Constraints: Important where installing an instrument in an already existing system.

8 Installation Process Proper space b/w CCD’s, to avoid beam clipping.
Pellicle Beamsplitters Pupil Plane Input Fiber SH WFS (14x14cm) Far Field CCD Spherical Mirror Flat Mirror 26 cm Iris Pupil Plane Proper space b/w CCD’s, to avoid beam clipping. WFS & Far Field Lens require a pupil plane. Far Field has to be located at the focal length of the lens. Calibration mode used for proof of principle. lens Pupil Plane Calibration you don’t have a lot

9 Data Types of Data Side by Side comparisons Proof of Principle WFS
Far Field Data Side by Side comparisons Proof of Principle 0.12 D neg. Cylinder

10 Proof of Principle: Defocus
Trial Lens: 0.12 D neg. defocus. Amount of defocus and spot size are directly proportional. Change in spot size Measured Simulated Measured PSF was what we expected . Simulated PSF was not what we expected, but we think that is due to limited sampling

11 Proof of Principle: Aberrator
Plastic bag- simulates higher order aberrations Qualitatively similar Would prefer quantitatively similar Improved by correlation or re-sampling

12 Conclusion & Future Directions
Far Field Camera is installed and working in calibration mode. Far Field data compares relatively well to the WFS data in calibration mode. Understand Calibration Error Investigate mitigation techniques to improve the performance of the AO-OCT system. Far Field Camera Software Adjust optical design (ghost reflections) Testing with model & human eye

13 Acknowledgements Dr. John S. Werner, UCD Dr. Julia W. Evans, UCD, LLNL
Dr. Robert J. Zawadzki, UCDMC Center for Adaptive Optics Dr. Patricia Mead, NSU Dr. Demetris Geddis, NSU Dr. Arlene Maclin, NSU References: R. J. Zawadzki et al., “Adaptive Optics- Optical Coherence Tomography: optimizing visualization of microscopic retinal structures in three dimensions,”J Opt. Soc. Am. A /Vol. 24, No. 5 (2007) J.W. Evans et al., “Characterization of an AO-OCT System,” Proceedings of the 6th International workshop on adaptive optics for Industry and Medicine : University of Galway, Ireland, June 2007. This work has been supported 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

14 Light Budget Light throughput is always important
Element measured power (mW) Reflectivity/ Transmistivity predicted power (mW) coupler 1.2 0.19 1.22 Collimation optics 0.98 1.20 achromatizing lens 1.17 aperture 0.85 1.00 pellicle 0.92 S1 0.87 0.90 Iris 0.78 S2 0.77 Bimorph DM 0.9 0.69 S3 0.67 0.68 S4 0.66 MEMS 0.7 0.46 S5 0.45 S6 0.44 Horiz scanner S7 0.43 S8 0.42 Vert scanner 0.41 S9 0.39 0.40 S10 Flat mirror Total to Eye 0.36 Light Budget Light throughput is always important 32% throughput in original system; 29% in current system Transmitted (%) Power ratio /Through put (%) Power ratio before Far Field (%) Pellicle 1 92 75 Pellicle 2 69.1 Bimorph DM 90 51.9 56 MEMS 70 34.9 37.9 Total input to the eye 29 31.7 Eveloping and error budget is a common tool for improved performance and system design in astronomical AO systems.

15 Extra Images Aberrator Extras


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