Endoscopic egomotion computation

Abstract

Computer assistance in Minimally Invasive Surgery is a very active field of research. Many systems designed for Computer Assisted Surgery require information about the instruments' positions and orientations. Our main focus lies on tracking a laparoscopic ultrasound probe to generate 3D ultrasound volumes. State-of-the-art tracking methods such as optical or electromagnetic tracking systems measure pose with respect to a fixed extra-body coordinate system. This causes inaccuracies of the reconstructed ultrasound volume in the case of patient motion, e.g. due to respiration. We propose attaching an endoscopic camera to the ultrasound probe and calculating the camera motion from the video sequence with respect to the organ surface. We adapt algorithms developed for solving the relative pose problem to recreate the camera path during the ultrasound sweep over the organ. By this image-based motion estimation camera motion can only be determined up to an unknown scale factor, known as the depth-speed-ambiguity. We show, how this problem can be overcome in the given scenario, exploiting the fact, that the distance of the camera to the organ surface is fixed and known. Preprocessing steps are applied to compensate for endoscopic image quality deficiencies

Laryngoscopic Image Stitching for View Enhancement and Documentation – First Experiences

“…Konen et al [10] suggested an approach for real-time mosaicking for neuro-endoscopic imagery. [11,12] describe a real time endoscopic stitching approach, based on KLT feature tracking, which has been applied to liver EPIs. Finally, an important contribution to this field is the work by Mountney and Yang [13] who suggest a simultaneous loca-tion and mapping approach (SLAM) for the real-time generation of EPIs.…”