4.7 Article

Automatic localization of endoscope in intraoperative CT image: A simple approach to augmented reality guidance in laparoscopic surgery

期刊

MEDICAL IMAGE ANALYSIS
卷 30, 期 -, 页码 130-143

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.media.2016.01.008

关键词

Augmented reality; C-arm; Registration; Intraoperative CT

资金

  1. University of Strasbourg
  2. IHU of Strasbourg

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The use of augmented reality in minimally invasive surgery has been the subject of much research for more than a decade. The endoscopic view of the surgical scene is typically augmented with a 3D model extracted from a preoperative acquisition. However, the organs of interest often present major changes in shape and location because of the pneumoperitoneum and patient displacement. There have been numerous attempts to compensate for this distortion between the pre- and intraoperative states. Some have attempted to recover the visible surface of the organ through image analysis and register it to the preoperative data, but this has proven insufficiently robust and may be problematic with large organs. A second approach is to introduce an intraoperative 3D imaging system as a transition. Hybrid operating rooms are becoming more and more popular, so this seems to be a viable solution, but current techniques require yet another external and constraining piece of apparatus such as an optical tracking system to determine the relationship between the intraoperative images and the endoscopic view. In this article, we propose a new approach to automatically register the reconstruction from an intraoperative CT acquisition with the static endoscopic view, by locating the endoscope tip in the volume data. We first describe our method to localize the endoscope orientation in the intraoperative image using standard image processing algorithms. Secondly, we highlight that the axis of the endoscope needs a specific calibration process to ensure proper registration accuracy. In the last section, we present quantitative and qualitative results proving the feasibility and the clinical potential of our approach. (C) 2016 Elsevier B.V. All rights reserved.

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