• DocumentCode
    2941979
  • Title

    Risk analysis for intraoperative liver surgery

  • Author

    Schwaiger, Johannes ; Markert, Mathias ; Seidl, Bernhard ; Shevchenko, Nikita ; Doerfler, Nikolas ; Lueth, Tim C.

  • Author_Institution
    Dept. of Micro Technol. & Med. Device Technol., Tech. Univ. Muenchen, Garching, Germany
  • fYear
    2010
  • fDate
    Aug. 31 2010-Sept. 4 2010
  • Firstpage
    410
  • Lastpage
    413
  • Abstract
    Hepatic vessel structure is very important to ensure the blood supply of the liver tissue. Therefore the knowledge of the hepatic vessel system is indispensable in liver surgery planning, for example before performing a liver resection. The purpose of this paper is to present an easy to use and fast method concerning hepatic vessel segmentation and risk analysis, which is intended to be applicable in clinical routine. Using CT scans vessels cannot be easily distinguished from other liver tissues. The segmentation algorithm used in this approach is mainly based on the arboreal structure of the hepatic vessel system. It is fully automatic and a prerequisite for the performance of a risk analysis concerning the minimal distances between tumors and vessels. A set of 20 oncological patient datasets was used to evaluate the segmentation algorithm and the risk analysis relating to their speed performance and ease of use, respectively. Segmentation algorithm was always performed in less than 1 minute and risk analysis even in less than 10 seconds. Each step was performed fully automatical. The obtained results show, that both segmentation algorithm and risk analysis are easy to use because no user interaction is required. In combination with the speed performance it is possible for the surgeon to accomplish a preoperative and intraoperative liver surgery planning on his own, respectively.
  • Keywords
    blood vessels; computerised tomography; image segmentation; liver; medical image processing; risk analysis; CT; blood supply; hepatic vessel structure; intraoperative liver surgery; liver tissue; risk analysis; segmentation algorithm; tumors; Algorithm design and analysis; Analytical models; Liver; Risk analysis; Surgery; Three dimensional displays; Tumors; Algorithms; Databases, Factual; Hepatic Veins; Humans; Image Processing, Computer-Assisted; Liver; Liver Diseases; Models, Biological; Preoperative Care; Risk Assessment; Tomography, X-Ray Computed;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
  • Conference_Location
    Buenos Aires
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4123-5
  • Type

    conf

  • DOI
    10.1109/IEMBS.2010.5627313
  • Filename
    5627313