[3-dimensional (3-D) visualization of the liver for planning extensive liver resections].
Klinik für Abdominal- und Transplantationschirurgie, Medizinische Hochschule, Hannover. Der Chirurg
(Impact Factor: 0.57).
Preoperative planning of liver resections in patients with liver tumors is based on sonography, computed tomography and magnetic resonance imaging. A new three-dimensional (3D) visualization program was developed based on CT data. This visualization program was used for preoperative planning in 6 patients with liver tumors in problematic intrahepatic localizations. In 5 out of 6 patients the liver resection could be performed as preoperatively planned. The intraoperative findings agreed with the 3D visualization in all these patients. 3D Visualization of the liver allowed clear and interactive planning of liver resections and improved the preparation of complex liver resections.
Available from: Volker Dicken
- "Furthermore, the pre-operative diagnostic data cannot be matched to the intraoperative situation using osseous landmarks [Grenacher L et al. 2005]. Concepts in the computer-assisted planning of surgery have been successfully driven forward in recent years, especially in the field of hepatic surgery [Lang H et al. 2005; Oldhafer KJ et al. 1999; Bornik A. et al. 2006]. The aims were to reduce the risks of surgery through pre-operative identification of structures that are at risk, as well as through predictions and minimization of the functional impairment to portions of tissue due to inadequate blood supply or backflow in the case of surgically induced disorders in the vascular system. "
Available from: Bernhard Preim
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ABSTRACT: The detection and the staging of tumors and their metastases in parenchymatous organs of the epigastric organs today is improved by the enormous increase of imaging system's efficiency. For an increasing number of findings, which shall be dissected in intention to cure, the feasibility of diagnostics and therapy-planning based on sonograms was investigated. In 3-D US image volumes of approx. 20 patients, characteristic anatomical structures (e.g., vessels, abscesses, tumors) were detected by specifically adapted automatic computer-based segmentation and visualized. The detection of pathological findings, their quantification and their spatial assignment to anatomical main structures was essentially simplified by 3-D image acquisition and 2-D and 3-D visualization of segmented images.
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