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Proceedings Paper

On pattern selection for laparoscope calibration
Author(s): Stephen Thompson; Yannic Meuer; Eddie Edwards; João Ramalhinho; Maria Ruxandra Robu; Danail Stoyanov; Sébastian Ourselin; Brian Davidson; David Hawkes; Matthew J. Clarkson
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Paper Abstract

Camera calibration is a key requirement for augmented reality in surgery. Calibration of laparoscopes provides two challenges that are not sufficiently addressed in the literature. In the case of stereo laparoscopes the small distance (less than 5mm) between the channels means that the calibration pattern is an order of magnitude more distant than the stereo separation. For laparoscopes in general, if an external tracking system is used, hand-eye calibration is difficult due to the long length of the laparoscope. Laparoscope intrinsic, stereo and hand-eye calibration all rely on accurate feature point selection and accurate estimation of the camera pose with respect to a calibration pattern. We compare 3 calibration patterns, chessboard, rings, and AprilTags. We measure the error in estimating the camera intrinsic parameters and the camera poses. Accuracy of camera pose estimation will determine the accuracy with which subsequent stereo or hand-eye calibration can be done. We compare the results of repeated real calibrations and simulations using idealised noise, to determine the expected accuracy of different methods and the sources of error. The results do indicate that feature detection based on rings is more accurate than a chessboard, however this doesn’t necessarily lead to a better calibration. Using a grid with identifiable tags enables detection of features nearer the image boundary, which may improve calibration.

Paper Details

Date Published: 3 March 2017
PDF: 13 pages
Proc. SPIE 10135, Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling, 101351W (3 March 2017); doi: 10.1117/12.2253717
Show Author Affiliations
Stephen Thompson, Univ. College London (United Kingdom)
Yannic Meuer, Univ. College London (United Kingdom)
Eddie Edwards, Univ. College London (United Kingdom)
João Ramalhinho, Univ. College London (United Kingdom)
Maria Ruxandra Robu, Univ. College London (United Kingdom)
Danail Stoyanov, Univ. College London (United Kingdom)
Sébastian Ourselin, Univ. College London (United Kingdom)
Brian Davidson, UCL Medical School (United Kingdom)
David Hawkes, Univ. College London (United Kingdom)
Matthew J. Clarkson, Univ. College London (United Kingdom)


Published in SPIE Proceedings Vol. 10135:
Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster; Baowei Fei, Editor(s)

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