Paper
30 May 2003 Intraoperative augmented reality for minimally invasive liver interventions
Michael Scheuering, Andrea Schenk, Armin Schneider, Bernhard Preim, Guenther Greiner
Author Affiliations +
Abstract
Minimally invasive liver interventions demand a lot of experience due to the limited access to the field of operation. In particular, the correct placement of the trocar and the navigation within the patient's body are hampered. In this work, we present an intraoperative augmented reality system (IARS) that directly projects preoperatively planned information and structures extracted from CT data, onto the real laparoscopic video images. Our system consists of a preoperative planning tool for liver surgery and an intraoperative real time visualization component. The planning software takes into account the individual anatomy of the intrahepatic vessels and determines the vascular territories. Methods for fast segmentation of the liver parenchyma, of the intrahepatic vessels and of liver lesions are provided. In addition, very efficient algorithms for skeletonization and vascular analysis allowing the approximation of patient-individual liver vascular territories are included. The intraoperative visualization is based on a standard graphics adapter for hardware accelerated high performance direct volume rendering. The preoperative CT data is rigidly registered to the patient position by the use of fiducials that are attached to the patient's body, and anatomical landmarks in combination with an electro-magnetic navigation system. Our system was evaluated in vivo during a minimally invasive intervention simulation in a swine under anesthesia.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael Scheuering, Andrea Schenk, Armin Schneider, Bernhard Preim, and Guenther Greiner "Intraoperative augmented reality for minimally invasive liver interventions", Proc. SPIE 5029, Medical Imaging 2003: Visualization, Image-Guided Procedures, and Display, (30 May 2003); https://doi.org/10.1117/12.480212
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Cited by 39 scholarly publications.
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KEYWORDS
Liver

Visualization

Surgery

Tumors

Image segmentation

Navigation systems

Veins

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