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Proceedings Paper

Endoscopic egomotion computation
Author(s): Tobias Bergen; Steffen Ruthotto; Stephan Rupp; Christian Winter; Christian Münzenmayer
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Paper Abstract

Computer assistance in Minimally Invasive Surgery is a very active field of research. Many systems designed for Computer Assisted Surgery require information about the instruments' positions and orientations. Our main focus lies on tracking a laparoscopic ultrasound probe to generate 3D ultrasound volumes. State-of-the-art tracking methods such as optical or electromagnetic tracking systems measure pose with respect to a fixed extra-body coordinate system. This causes inaccuracies of the reconstructed ultrasound volume in the case of patient motion, e.g. due to respiration. We propose attaching an endoscopic camera to the ultrasound probe and calculating the camera motion from the video sequence with respect to the organ surface. We adapt algorithms developed for solving the relative pose problem to recreate the camera path during the ultrasound sweep over the organ. By this image-based motion estimation camera motion can only be determined up to an unknown scale factor, known as the depth-speed-ambiguity. We show, how this problem can be overcome in the given scenario, exploiting the fact, that the distance of the camera to the organ surface is fixed and known. Preprocessing steps are applied to compensate for endoscopic image quality deficiencies.

Paper Details

Date Published: 12 March 2010
PDF: 8 pages
Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76232J (12 March 2010); doi: 10.1117/12.844689
Show Author Affiliations
Tobias Bergen, Fraunhofer Institute for Integrated Circuits (Germany)
Steffen Ruthotto, Fraunhofer Institute for Integrated Circuits (Germany)
Stephan Rupp, Fraunhofer Institute for Integrated Circuits (Germany)
Christian Winter, Fraunhofer Institute for Integrated Circuits (Germany)
Christian Münzenmayer, Fraunhofer Institute for Integrated Circuits (Germany)


Published in SPIE Proceedings Vol. 7623:
Medical Imaging 2010: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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