15 March 2013 A graph-based approach for local and global panorama imaging in cystoscopy
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Abstract
Inspection of the urinary bladder with an endoscope (cystoscope) is the usual procedure for early detection of bladder cancer. The very limited field of view provided by the endoscope makes it challenging to ensure, that the interior bladder wall has been examined completely. Panorama imaging techniques can be used to assist the surgeon and provide a larger view field. Different approaches have been proposed, but generating a panorama image of the entire bladder from real patient data is still a challenging research topic. We propose a graph-based and hierarchical approach to assess this problem to first generate several local panorama images, followed by a global textured three-dimensional reconstruction of the organ. In this contribution, we address details of the first level of the approach including a graph-based algorithm to deal with the challenging condition of in-vivo data. This graph strategy gives rise to a robust relocalization strategy in case of tracking failure, an effective keyframe selection process as well as the concept of building locally optimized sub-maps, which lay the ground for a global optimization process. Our results show the successful application of the method to four in-vivo data sets.
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Tobias Bergen, Thomas Wittenberg, Christian Münzenmayer, Chi Chiung Grace Chen, Gregory D. Hager, "A graph-based approach for local and global panorama imaging in cystoscopy", Proc. SPIE 8671, Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling, 86711K (15 March 2013); doi: 10.1117/12.2008174; https://doi.org/10.1117/12.2008174
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