Retinal Imaging Protocols for Constructing High Resolution Mosaics of In Vivo Photoreceptor Cells Blanca E. Marinez Cabrillo College Aptos, California.

Slides:



Advertisements
Similar presentations
Human-Computer Interaction
Advertisements

Introduction to Eye Tracking
Visual Field Examinations
Lecture 11. Microscopy. Optical or light microscopy involves passing visible light transmitted through or reflected from the sample through a single or.
LIGHT AND THE RETINAL IMAGE: KEY POINTS Light travels in (more or less) straight lines: the pinhole camera’s inverted image Enlarging the pinhole leads.
SPECTRALIS® Glaucoma Module Premium Edition
The eye – curved cornea – lens – retina – fovea – optic disk Using Light.
Color Perception Combined rod + cone response yields both color and brightness perception Cell responses vary with illumination conditions: –low light.
Perception of Stimuli Stephen Taylor.
Research on high-definition video vehicles location and tracking Xiong Changzhen, LiLin IEEE, Distributed Computing and Applications to Business Engineering.
Correlation Between Image Reproduction Preferences and Viewing Patterns Measured with a Head Mounted Eye Tracker Lisa A. Markel Jeff B. Pelz, Ph.D. Center.
Retinal Scanning Biometrics Presentation by Ajinkya Bhave 30 th April, 2003.
Registration-Based Change Detection Charles V. Stewart Department of Computer Science Rensselaer Polytechnic Institute.
1 Computer Science 631 Lecture 6: Color Ramin Zabih Computer Science Department CORNELL UNIVERSITY.
The visual system Lecture 1: Structure of the eye
A Vision-Based System that Detects the Act of Smoking a Cigarette Xiaoran Zheng, University of Nevada-Reno, Dept. of Computer Science Dr. Mubarak Shah,
Major transformations of the light signal in the retina: 1.Temporal filtering – visual response slower than input signal. 2. Spatial filtering – local.
Evaluation of a Scanned Laser Display as an Alternative Low Vision Computer Interface Conor Kleweno, Eric Seibel, Ph.D., Kyle Kloeckner, Bob Burstein,
Active Vision Key points: Acting to obtain information Eye movements Depth from motion parallax Extracting motion information from a spatio-temporal pattern.
Dr. Ayesha Abdullah Learning outcomes By the end of this lecture the students would be able to; Identify the common symptoms and signs of VR.
112/03/2004 Vision-Realistic Rendering: Simulation of the Scanned Foveal Image from Wavefront Data of Human Subjects, Brian A. Barsky, 2004 Gazihan Alankus.
A Human Eye Retinal Cone Synthesizer Michael F. Deering.
Visual Processing by the Retina. the retina bears careful examination for several reasons : First, it is useful for understanding sensory transduction.
Computer Vision – Fundamentals of Human Vision Hanyang University Jong-Il Park.
© by Yu Hen Hu 1 Human Visual System. © by Yu Hen Hu 2 Understanding HVS, Why? l Image is to be SEEN! l Perceptual Based Image Processing.
“Twinkle, Twinkle Little Star”: An Introduction to Adaptive Optics Mt. Hamilton Visitor’s Night July 28, 2001.
Human Visual Perception The Human Eye Diameter: 20 mm 3 membranes enclose the eye –Cornea & sclera –Choroid –Retina.
Digital Image Fundamentals. What Makes a good image? Cameras (resolution, focus, aperture), Distance from object (field of view), Illumination (intensity.
Austin Roorda, Ph.D. University of Houston College of Optometry
Biometrics Stephen Schmidt Brian Miller Devin Reid.
Eye is the window to our soul. English physicist Sir Isaac Newton, in an experiment, observed that a ray of sunlight, or white light, was broken up into.
Dr. Ayesha Abdullah Learning outcomes By the end of this lecture the students would be able to; Correlate the structural organization of the.
Stylization and Abstraction of Photographs Doug Decarlo and Anthony Santella.
Optical Coherence Tomography for Retinal Imaging ECE 172A Julio Flores.
Dr. Engr. Sami ur Rahman Digital Image Processing Lecture 2: Visual System.
FIBER-OPTIC LASER INTERFEROMETER FOR VISION RESEARCH Timne Bilton PI & Supervisor: Dr. David Williams Collaborators: Julianna Lin, Silvestre Manzanera.
Actuator 2 – Provides rotation about the roll direction. Actuator 1 – Provides rotation about the pitch direction Figure 2: The Linear Actuator model Abstract.
CSE 185 Introduction to Computer Vision Stereo. Taken at the same time or sequential in time stereo vision structure from motion optical flow Multiple.
Visually guided attention during flying OR Pilots “do not like” fovea because they cannot pay attention to more than 1% of space at any one time.
DECREASED FLICKER SENSITIVITY WITH A SCANNED LASER DISPLAY. J.P. Kelly 1, H.L. Pryor, E.S. Viirre, T. Furness III. 1 Children's Hospital & Medical Center;
Structure of the lens The fibrous nature of the lens is evident in low- magnification scanning Lens fibers (micrograph 2) are mature cells that have lost.
Option E: Neurobiology and Behavior. E.2.1 Outline the diversity of stimuli that can be detected by human sensory receptors, including mechanoreceptors,
Virtual University - Human Computer Interaction 1 © Imran Hussain | UMT Imran Hussain University of Management and Technology (UMT) Lecture 7 Human Input-Output.
Why isn’t vision perfect? An exercise in psychoanatomy.
Virtual Retinal Display (VRD) Emulator Test System H.L. Pryor, B. Burstein, J. Kollin, E.S. Viirre, E. Seibel, J.P. Kelly, T. Furness III. Human Interface.
Marilyn Zúñiga Advisor: Dr. Roorda Supervisor: Dr. Grieve Site: University of California-Berkeley Imaging Intrinsic Signals in the Retina Using Different.
Seeing READING ASSIGNMENT Discussion of Gregory’s Article on Visual Illusions – Tues Feb 17 Available in your course pack.
Human Visual System.
The Human Retina. Retina Function To detect movement To detect color To detect detail.
Student : Chen–Fung Tsen Advisor : Sheng-Lung Huang.
Date of download: 6/2/2016 Copyright © 2016 American Medical Association. All rights reserved. From: Spectral Domain Optical Coherence Tomography: Ultra-high.
Optical Instruments II Instruments for Imaging the Retina.
Date of download: 6/25/2016 Copyright © 2016 American Medical Association. All rights reserved. From: Normal Macular Thickness Measurements in Healthy.
Southwest Center for Microsystems Education
Southwest Center for Microsystems Education
Capturing Light… in man and machine
From: An Automated Reference Frame Selection (ARFS) Algorithm for Cone Imaging with Adaptive Optics Scanning Light Ophthalmoscopy Trans. Vis. Sci. Tech..
CS4670 / 5670: Computer Vision Kavita Bala Lec 27: Stereo.
WIDE-FIELD BEDSIDE IMAGING OF THE HUMAN RETINA USING A SMARTPHONE HOLDER LIANNA M. VALDES,* DOV B. SEBROW,* ERIC L. TONG,† AND TONGALP H. TEZEL* METHODS:
From: In Vivo Imaging of Microscopic Structures in the Rat Retina
Invest. Ophthalmol. Vis. Sci ;48(7): doi: /iovs Figure Legend:
From: Effects of Intraframe Distortion on Measures of Cone Mosaic Geometry from Adaptive Optics Scanning Light Ophthalmoscopy Trans. Vis. Sci. Tech ;5(1):10.
Anatomy of the Eye: II histology and retinal landmarks
Early Processing in Biological Vision
Counting in High-Density Crowd Videos
Vision: Two Speeds in the Retina
Option E: Neurobiology and Behavior
Detection of salient points
Option E: Neurobiology and Behavior
Presentation transcript:

Retinal Imaging Protocols for Constructing High Resolution Mosaics of In Vivo Photoreceptor Cells Blanca E. Marinez Cabrillo College Aptos, California Thomas Hebert, Austin Roorda, College of Optometry, University of Houston, Houston, Tx.

Why is retinal imaging important? Retinal imaging, the process of obtaining detailed images of the retina, it is important for: Early diagnosis of retinal diseases. Monitoring the progression of retinal diseases. Studying the distribution of photoreceptors throughout the retina. AOSLO Image 1.5x1.4 deg Courtesy: Austin Roorda

How is retinal imaging possible? Adaptive Optics Scanning Laser Ophthalmoscope (AOSLO) wavefrontsensing lightdelivery wavefrontcompensation lightdetection rasterscanning eye Courtesy: Austin Roorda

M O S A I C S To Construct a mosaic…Why is the protocol important? High correlation between images is important when matching them. THE B I G PICTURE…

M O S A I C S To Construct a mosaic…Why is the protocol important? High correlation between images is important when matching them. THE B I G PICTURE…

M O S A I C S To Construct a mosaic…Why is the protocol important? High correlation between images is important when matching them. THE B I G PICTURE…

M O S A I C S To Construct a mosaic…Why is the protocol important? High correlation between images is important when matching them. THE B I G PICTURE…

M O S A I C S To Construct a mosaic…Why is the protocol important? High correlation between images is important when matching them. (Images from different protocols) The protocol affects the clarity of the images, the ability of the subject to fixate well, the region of the retina being imaged and the problems when creating the mosaic. THE B I G PICTURE…

AOSLO Image 1.5x1.4 deg Courtesy: Austin Roorda This shows a mosaic of approximately 9x9 degrees co-aligned with the same region of the fundus photograph.

Targets allow you to map the region of the retina that you want to image and to keep track of where your images should match when constructing the mosaic. P r o t o c o l It’s what you look at… how you look at it... And how we collect the data.

P r o t o c o l It’s what you look at… how you look at it... And how we collect the data. The subject can fixate at one point of the target, gaze across given points or line on the target, or follow a moving point of light like a laser. Video of a subject gazing across a line on a target.

P r o t o c o l It’s what you look at… how you look at it... And how we collect the data. The subject can fixate at one point of the target, gaze across given points or line on the target, or follow a moving point of light like a laser. Video of a subject fixating at one point of the target.

P r o t o c o l It’s what you look at… how you look at it... And how we collect the data. The length of your videos. You may vary: The number of images you register and sum for each location. The number of videos you take.

Protocol A Target Twenty-five videos, twenty seconds each.

Protocol A Drastic difference in intensity of photoreceptors in the two images. Low correlation between images. Edges are more prominent. Courtesy: Ramesh Sundaram KV

Protocol B Target Ten continuous videos where the subject gazes across given points.

Protocol B RS Noticeable change in images from different videos. Good foveal region due to the amount of videos taken at the fovea. When constructing the mosaic there was a high correlation between images of the same video but not between corresponding images of different videos.

Protocol C Target One continuous video where the subject gazes across lines 1-11.

Protocol C RS The mosaic shows uniform brightness. Edges are not prominent. High correlation between images. The subject had difficulties gazing across the lines. Fixation on the central region was minimal therefore we didn’t get a good image of the foveal region.

Protocol D Target One continuous video where the subject followed a laser point move along lines

Protocol D RS The mosaic shows uniform brightness. Edges are not prominent High correlation between images. Subject could fixate well following the laser across the lines. Fixation on the central region was minimal therefore we didn’t get a good image of the foveal region.

C o n c l u s i o n Subjectively, the best results were given by Protocol D. This protocol allows the subject to fixate well and it minimizes the effect of change in reflectivity of photoreceptors due to time difference in which the images were captured. It also allows us to match common features of neighboring frames more accurately. This creates a mosaic that is uniform in brightness, that has less visible edges, and easy to construct.

Acknowledgments Center for Adaptive Optics National Science Foundation #AST Dr. Tom Hebert Dr. Austin Roorda Dr. Fernando Romero Ramesh Sundaram Dr. Krishnakumar Venkateswaran Siddharth Poonja The Roorda Lab