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Proceedings Paper

3D surface reconstruction for laparoscopic computer-assisted interventions: comparison of state-of-the-art methods
Author(s): A. Groch; A. Seitel; S. Hempel; S. Speidel; R. Engelbrecht; J. Penne; K. Höller; S. Röhl; K. Yung; S. Bodenstedt; F. Pflaum; T. R. dos Santos; S. Mersmann; H.-P. Meinzer; J. Hornegger; L. Maier-Hein
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Paper Abstract

One of the main challenges related to computer-assisted laparoscopic surgery is the accurate registration of pre-operative planning images with patient's anatomy. One popular approach for achieving this involves intraoperative 3D reconstruction of the target organ's surface with methods based on multiple view geometry. The latter, however, require robust and fast algorithms for establishing correspondences between multiple images of the same scene. Recently, the first endoscope based on Time-of-Flight (ToF) camera technique was introduced. It generates dense range images with high update rates by continuously measuring the run-time of intensity modulated light. While this approach yielded promising results in initial experiments, the endoscopic ToF camera has not yet been evaluated in the context of related work. The aim of this paper was therefore to compare its performance with different state-of-the-art surface reconstruction methods on identical objects. For this purpose, surface data from a set of porcine organs as well as organ phantoms was acquired with four different cameras: a novel Time-of-Flight (ToF) endoscope, a standard ToF camera, a stereoscope, and a High Definition Television (HDTV) endoscope. The resulting reconstructed partial organ surfaces were then compared to corresponding ground truth shapes extracted from computed tomography (CT) data using a set of local and global distance metrics. The evaluation suggests that the ToF technique has high potential as means for intraoperative endoscopic surface registration.

Paper Details

Date Published: 2 March 2011
PDF: 9 pages
Proc. SPIE 7964, Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, 796415 (2 March 2011); doi: 10.1117/12.878354
Show Author Affiliations
A. Groch, German Cancer Research Ctr. (Germany)
A. Seitel, German Cancer Research Ctr. (Germany)
S. Hempel, Technische Univ. München (Germany)
Friedrich-Alexander-Univ. Erlangen-Nürnberg (Germany)
S. Speidel, Karlsruhe Institute of Technology (Germany)
R. Engelbrecht, Friedrich-Alexander-Univ. Erlangen-Nürnberg (Germany)
J. Penne, Technische Univ. München (Germany)
K. Höller, Friedrich-Alexander-Univ. Erlangen-Nürnberg (Germany)
Technische Univ. München (Germany)
S. Röhl, Karlsruhe Institute of Technology (Germany)
K. Yung, German Cancer Research Ctr. (Germany)
S. Bodenstedt, Karlsruhe Institute of Technology (Germany)
F. Pflaum, Friedrich-Alexander-Univ. Erlangen-Nürnberg (Germany)
T. R. dos Santos, German Cancer Research Ctr. (Germany)
S. Mersmann, German Cancer Research Ctr. (Germany)
H.-P. Meinzer, German Cancer Research Ctr. (Germany)
J. Hornegger, Friedrich-Alexander-Univ. Erlangen-Nürnberg (Germany)
L. Maier-Hein, German Cancer Research Ctr. (Germany)


Published in SPIE Proceedings Vol. 7964:
Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling
Kenneth H. Wong; David R. Holmes, Editor(s)

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