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Robust feature tracking for endoscopic pose estimation and structure recovery

 
: Speidel, S.; Krappe, S.; Röhl, S.; Bodenstedt, S.; Müller-Stich, B.; Dillmann, R.

:

Holmes, D.R. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Medical imaging 2013. Image-guided procedures, robotic interventions, and modeling : 12 - 14 February 2013, Lake Buena Vista, Florida, United States
Bellingham, WA: SPIE, 2013 (Proceedings of SPIE 8671)
ISBN: 978-0-8194-9445-0
Paper 867102
Image-Guided Procedures, Robotic Interventions, and Modeling Conference <2013, Lake Buena Vista/Fla.>
Englisch
Konferenzbeitrag
Fraunhofer IIS ()

Abstract
Minimally invasive surgery is a highly complex medical discipline with several difficulties for the surgeon. To alleviate these difficulties, augmented reality can be used for intraoperative assistance. For visualization, the endoscope pose must be known which can be acquired with a SLAM (Simultaneous Localization and Mapping) approach using the endoscopic images. In this paper we focus on feature tracking for SLAM in minimally invasive surgery. Robust feature tracking and minimization of false correspondences is crucial for localizing the endoscope. As sensory input we use a stereo endoscope and evaluate different feature types in a developed SLAM framework. The accuracy of the endoscope pose estimation is validated with synthetic and ex vivo data. Furthermore we test the approach with in vivo image sequences from da Vinci interventions.

: http://publica.fraunhofer.de/dokumente/N-254774.html