Statistical Shape Models for Grasp Point Determination in Laparoscopic Surgeries
Kunz CP, Kraus M, Younis R, Wagner M, Mathis-Ullrich F (2024)
Publication Type: Journal article
Publication year: 2024
Journal
Book Volume: 10
Pages Range: 41-44
Journal Issue: 1
Abstract
Robotic assistance systems are being used more and more frequently in the operating room, with the goal to support surgeons and to automate parts of a procedure. The laparoscopic cholecystectomy is one of the most common procedures in Germany.We aim to automate the assistant grasp task in this procedure. To achieve this goal, first the grasp points on the gallbladder need to be determined. In this work, we therefore present a statistical shape model fitting to the gallbladder for grasp point determination. Gallbladder and liver point clouds are utilized as inputs. A registration algorithm is used to fit the shape model to the gallbladder mesh. The process is evaluated on three different datasets achieving a successful grasping point identification of 90% for artificially created gallbladders, 100% for our silicon phantom model, and 90% for ex-vivo organs.
Authors with CRIS profile
Christian-Peter Kunz
Professur für Robotische Planung und Kognition in der Chirurgie
Franziska Mathis-Ullrich
Professur für Robotische Planung und Kognition in der Chirurgie
Involved external institutions
Karlsruhe Institute of Technology (KIT)
Germany (DE)
Universitätsklinikum Carl Gustav Carus Dresden
Germany (DE)
Germany (DE)
Universitätsklinikum Carl Gustav Carus Dresden
Germany (DE)
How to cite
APA:
Kunz, C.-P., Kraus, M., Younis, R., Wagner, M., & Mathis-Ullrich, F. (2024). Statistical Shape Models for Grasp Point Determination in Laparoscopic Surgeries. Current Directions in Biomedical Engineering, 10(1), 41-44. https://doi.org/10.1515/cdbme-2024-0111
MLA:
Kunz, Christian-Peter, et al. "Statistical Shape Models for Grasp Point Determination in Laparoscopic Surgeries." Current Directions in Biomedical Engineering 10.1 (2024): 41-44.
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