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Advanced visualization techniques for laparoscopic liver surgery
Linköping University, Department of Physics, Chemistry and Biology, Complex Materials and Devices. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
Visual Computing Group, Ulm University.
2015 (English)In: Proceedings of SIGRAD 2015: June 1st and 2nd, Stockholm, Sweden / [ed] Christopher E. Peters, Lars Kjelldahl, Stockholm: Svenska föreningen för grafisk databehandling , 2015, 28-31 p.Conference paper (Refereed)
Abstract [en]

In order to make it easier for the surgeons to locate tumors during a laparoscopic liver surgery, and to form a mental image of the remaining structures, the 3D models of the liver’s inner structures are extracted from a preoperative CT scan and are overlaid onto the live video stream obtained during surgery. In that way the surgeons can virtually look into the liver and locate the tumors (focus objects) and also have a basic understanding of their spatial relation with other critical structures. Within this paper, we present techniques for enhancing the spatial comprehension of the focus objects in relation to their surrounding areas, while they are overlaid onto the live endoscope video stream. To obtain an occlusion-free view while not destroying the context, we place a cone on the position of each focus object facing the camera. The cone creates an intersection surface (cut volume) that cuts the structures, visualizing the depth of the cut and the spatial relation between the focus object and the intersected structures. Furthermore, we combine this technique with several rendering approaches, which have proven to be useful for enhancing depth perception in other scenarios.

Place, publisher, year, edition, pages
Stockholm: Svenska föreningen för grafisk databehandling , 2015. 28-31 p.
Series
Linköping Electronic Conference Proceedings, ISSN 1650-3686 (print), 1650-3740 (online) ; 120
Keyword [en]
Visualization, Tumor detection, depth perception
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-131261ISBN: 9789176858554OAI: oai:DiVA.org:liu-131261DiVA: diva2:968857
Conference
SIGRAD 2015, June 1st and 2nd, Stockholm, Sweden
Available from: 2016-09-13 Created: 2016-09-13 Last updated: 2016-09-13Bibliographically approved

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Felekidis, DimitriosSteneteg, Peter
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