Dense Surface Reconstruction for Enhanced Navigation in MIS View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2011

AUTHORS

Johannes Totz , Peter Mountney , Danail Stoyanov , Guang-Zhong Yang

ABSTRACT

Recent introduction of dynamic view expansion has led to the development of computer vision methods for minimally invasive surgery to artificially expand the intra-operative field-of-view of the laparoscope. This provides improved awareness of the surrounding anatomical structures and minimises the effect of disorientation during surgical navigation. It permits the augmentation of live laparoscope images with information from previously captured views. Current approaches, however, can only represent the tissue geometry as planar surfaces or sparse 3D models, thus introducing noticeable visual artefacts in the final rendering results. This paper proposes a high-fidelity tissue geometry mapping by combining a sparse SLAM map with semi-dense surface reconstruction. The method is validated on phantom data with known ground truth, as well as in-vivo data captured during a robotic assisted MIS procedure. The derived results have shown that the method is able to effectively increase the coverage of the expanded surgical view without compromising mapping accuracy. More... »

PAGES

89-96

References to SciGraph publications

  • 2006. Real-Time Endoscopic Mosaicking in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2006
  • 2008. Dynamic View Expansion for Enhanced Navigation in Natural Orifice Transluminal Endoscopic Surgery in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2008
  • 2012-05. Enhanced visualisation for minimally invasive surgery in INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
  • 2010. GPU-Accelerated Robotic Intra-operative Laparoscopic 3D Reconstruction in INFORMATION PROCESSING IN COMPUTER-ASSISTED INTERVENTIONS
  • 2010. Real-Time Stereo Reconstruction in Robotically Assisted Minimally Invasive Surgery in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2010
  • 2010. A Robust Mosaicing Method with Super-Resolution for Optical Medical Images in MEDICAL IMAGING AND AUGMENTED REALITY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-23623-5_12

    DOI

    http://dx.doi.org/10.1007/978-3-642-23623-5_12

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1044995001

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/22003604


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