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Laparoscope self-calibration for robotic assisted minimally invasive surgery

Danail Stoyanov, Ara Darzi, Guang-Zhong Yang

Conference or Workshop Paper
Medical Image Computing and Computer Assisted Intervention (MICCAI05)
2005
pp.114–121
Abstract

For robotic assisted minimal access surgery, recovering 3D soft tissue deformation is important for intra-operative surgical guidance, motion compensation, and prescribing active constraints. We propose in this paper a method for determining varying focal lengths of stereo laparoscope cameras during robotic surgery. Laparoscopic images typically feature dynamic scenes of soft-tissue deformation and self-calibration is difficult with existing approaches due to the lack of rigid temporal constraints. The proposed method is based on the direct derivation of the focal lengths from the fundamental matrix of the stereo cameras with known extrinsic parameters. This solves a restricted self-calibration problem, and the introduction of the additional constraints improves the inherent accuracy of the algorithm. The practical value of the method is demonstrated with analysis of results from both synthetic and in vivo data sets.

BibTEX file for the publication
 

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