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Copyright (c) 2023 Proceedings on Automation in Medical Engineering
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Minimally invasive surgery enables fast and secure interventions, especially when stereoscopic laparoscopes are used which generate 3D images and depth perception for surgeons. A further step could be image-guided laparoscopy, machine-learning-based tumor detection and autonomous robotic surgery. These applications require geometric information, like depth, of the affected organ surfaces, called surface reconstruction. Depending on the use case, the surface reconstruction must be highly accurate in submillimeter scope. A stereoscope might achieve this in combination with structured light. This paper explores two different light sources that generate random patterns which assist stereo matching algorithms in case of poorly structured and challenging environments. The experiment includes a stereo laparoscope, a folded white paper and a structured light producing source. In set-up A, a laser with a diffractive optical element is deployed. Set-up B inserts a digital light processing projector. Both light sources generate a random pattern onto the organ´s surface which is detected by stereo matching algorithms. The analysis of both results shows that the digital light processing projector outperforms the laser.