Design Considerations for a Computer-Vision-Enabled Ophthalmic Augmented Reality Environment

Jeffrey W. Berger1,2,5, Michael E. Leventon3,4, Nobuhiko Hata4,
William Wells3,4,5, Ron Kikinis4,5

1. Department of Ophthalmology, Scheie Eye Institute, University of Pennsylvania, Philadelphia PA 19104 USA
2. Massachusetts Eye and Ear Infirmary, Boston MA 02114 USA
3. AI Lab, MIT, 545 Technology Sq, Cambridge MA 02139 USA
4. Dept. of Radiology, Brigham and Womens Hospital, Boston MA 02115 USA
5. Harvard Medical School, Boston MA 02115 USA

Abstract:

We have initiated studies towards the design and implementation of an ophthalmic augmented reality environment in order to allow for a) more precise laser treatment for ophthalmic diseases, b) teaching, c) telemedicine, and d) real-time image measurement, analysis, and comparison. The proposed system is being designed around a standard slit-lamp biomicroscope. The microscope will be interfaced to a CCD camera, and the image sent to a video capture board. A single computer workstation will coordinate image capture, registration, and display. The captured image is registered with previously stored, montaged photographic and angiographic data, with superposition facilitated by fundus-landmark-based fast registration algorithms. The computer then drives a high intensity, VGA resolution video display with adjustable brightness and contrast attached to one of the oculars of the slitlamp biomicroscope. Preliminary studies with a modified binocular operating microscope interfaced to a Sun Ultra1 Workstation and an IBM-compatible PC demonstrates proof-of-principle. Robust, accurate fundus image montaging is accomplished with Hausdorff-distance-based methods. For photographic and angiographic data where the vessel gray levels vary from light to dark, and intensity-based correlation methods fail, image-preprocessing with smoothing, edge-detection, and thresholding facilitates registration. Non-real-time registration ( CPU seconds) is achieved by non-optimized simple template matching (translation only, Matrox Inspector) or Hausdorff-distance-based (translation, rotation, and scale) algorithms performed on edge-detected fundus photographic and angiographic images, and on images of a model eye. Successful registration and image overlay of color, monochromatic, and angiographic images is demonstrated. To our knowledge, these studies represent the first investigation towards design and implementation of an ophthalmic augmented reality environment.

• Introduction
• Methods
  • Engineering Considerations
  • Montaging
  • Registration
  • Image Overlay
• Results
• Discussion
• References
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