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  4. 3D-Scan hole detection for robot-assisted laparoscopic surgery
 
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2025
Journal Article
Title

3D-Scan hole detection for robot-assisted laparoscopic surgery

Abstract
Minimally invasive laparoscopic surgery, where endoscopes and instruments are inserted through small incisions, has advanced to the next stage of development: robot-assisted minimally invasive surgery. These systems use a camera and robotic manipulators operated by human surgeons through human-in-the-loop control. To further improve surgical precision and autonomy, data-driven assistance must be expanded. One promising approach is 3D reconstruction based on endoscopic images. A 30°endoscope tip enhances the field of view by enabling rotational motion around the instrument’s axis. However, when performing a 3D scan with such an endoscope, a blind spot inherently forms along the shaft axis, creating a region that cannot be captured during rotation. Additional missing data may arise due to occlusions from anatomical geometry and the specific endoscope pose during a scan. These limitations result in incomplete 3D reconstructions, which can negatively impact surgical navigation and decision-making. This paper presents a method tailored to medical applications for detecting and characterizing holes in laparoscopic 3D scans. The proposed method uses geometric analysis of the point cloud to identify regions of sparse or missing data and correlates these gaps with endoscope positioning and anatomical visibility. It is designed to operate robustly on high-density point clouds generated by advanced laparoscopic 3D reconstruction systems. By integrating robotic control, our method provides a foundation for adaptive endoscope repositioning to recover missing views and improve reconstruction completeness. The proposed method paves the way towards fast (5 s) feedback for optimized 3D scanning in laparoscopic environments.
Author(s)
Göbel, Birthe
University of Freiburg
Richter, Alexander
Fraunhofer-Institut für Kurzzeitdynamik Ernst-Mach-Institut EMI  
Rupitsch, Stefan
University of Freiburg
Reiterer, Alexander  
Fraunhofer-Institut für Physikalische Messtechnik IPM  
Möller, Knut
Furtwangen University
Journal
IFAC Journal of Systems and Control  
Open Access
DOI
10.1016/j.ifacsc.2025.100336
Additional full text version
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Language
English
Fraunhofer-Institut für Physikalische Messtechnik IPM  
Fraunhofer-Institut für Kurzzeitdynamik Ernst-Mach-Institut EMI  
Keyword(s)
  • Computer vision

  • Minimally invasive surgery

  • 3D reconstruction

  • Hole detection

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