Intraoperative on-the-fly organ-mosaicking for laparoscopic surgery

• Verfasst von: Reichard, Daniel [VerfasserIn]
• Verfasst von: Bodenstedt, Sebastian [VerfasserIn]
• Verfasst von: Suwelack, Stefan [VerfasserIn]
• Verfasst von: Mayer, Benjamin [VerfasserIn]
• Verfasst von: Preukschas, Anas [VerfasserIn]
• Verfasst von: Wagner, Martin [VerfasserIn]
• Verfasst von: Kenngott, Hannes Götz [VerfasserIn]
• Verfasst von: Müller, Beat P. [VerfasserIn]
• Verfasst von: Dillmann, Rüdiger [VerfasserIn]
• Verfasst von: Speidel, Stefanie [VerfasserIn]
• Titel: Intraoperative on-the-fly organ-mosaicking for laparoscopic surgery
• Verf.angabe: Daniel Reichard, Sebastian Bodenstedt, Stefan Suwelack, Benjamin Mayer, Anas Preukschas, Martin Wagner, Hannes Kenngott, Beat Müller-Stich, Rüdiger Dillmann, Stefanie Speidel
• E-Jahr: 2015
• Jahr: 10 December 2015
• Umfang: ?
• Fussnoten: Gesehen am 17.06.2020
• Titel Quelle: Enthalten in: Journal of medical imaging
• Ort Quelle: [Bellingham, Wash.] : SPIE, 2014
• Jahr Quelle: 2015
• Band/Heft Quelle: 2(2015,4) Artikel-Nummer 045001
• ISSN Quelle: 2329-4310
• DOI: doi:10.1117/1.JMI.2.4.045001
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1700747894

Abstract

The goal of computer-assisted surgery is to provide the surgeon with guidance during an intervention, e.g., using augmented reality. To display preoperative data, soft tissue deformations that occur during surgery have to be taken into consideration. Laparoscopic sensors, such as stereo endoscopes, can be used to create a three-dimensional reconstruction of stereo frames for registration. Due to the small field of view and the homogeneous structure of tissue, reconstructing just one frame, in general, will not provide enough detail to register preoperative data, since every frame only contains a part of an organ surface. A correct assignment to the preoperative model is possible only if the patch geometry can be unambiguously matched to a part of the preoperative surface. We propose and evaluate a system that combines multiple smaller reconstructions from different viewpoints to segment and reconstruct a large model of an organ. Using graphics processing unit-based methods, we achieved four frames per second. We evaluated the system with in silico, phantom, ex vivo, and in vivo (porcine) data, using different methods for estimating the camera pose (optical tracking, iterative closest point, and a combination). The results indicate that the proposed method is promising for on-the-fly organ reconstruction and registration.