Tracking intraocular microdevices based on colorspace evaluation and statistical color/shape information

Authors:
Christos Bergeles;Georgios Fagogenis;Jake J. Abbott;Bradley J. Nelson
Affiliations:
Institute of Robotics and Intelligent Systems, ETH Zurich, Zurich, Switzerland;Institute of Robotics and Intelligent Systems, ETH Zurich, Zurich, Switzerland;Department of Mechanical Engineering, University of Utah, Salt Lake City, Utah and Institute of Robotics and Intelligent Systems, ETH Zurich, Zurich, Switzerland;Institute of Robotics and Intelligent Systems, ETH Zurich, Zurich, Switzerland
Venue:
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Year:
2009

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Abstract

Successful ophthalmic surgeries using intraocular untethered microrobots or tethered robotic microtools require methods to robustly track the microdevices in the posterior of the human eye. The dimensions and specularities of the microdevices are major obstacles for accurate tracking. In addition, the optical structure of the human eye makes it challenging to keep the objects of interest constantly in focus, resulting in blurred images. In this paper, the advantages of using different colorspacaes for intraocular tracking are examined. After selection of the appropriate colorspace, thresholds that ensure maximum separation of the device from the background are calculated. Based on trained color histograms, level sets are used to track in real time, and the use of statistical shape information is incorporated in the existing tracking framework. The efficacy of the algorithm is demonstrated by tracking a microrobot in a model eye, using a custom made ophthalmoscope and off-the-shelf opthalmoscopy lenses. With the appropriate colorspace and threshold selection, tracking errors are minimized and are further diminished using shape information.