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  4. Accurate physics-based registration for the outcome validation of minimal invasive interventions and open liver surgeries
 
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2017
Journal Article
Title

Accurate physics-based registration for the outcome validation of minimal invasive interventions and open liver surgeries

Abstract
The purpose of this paper is to present an outcome validation tool for tumor radiofrequency (RF) ablation and resection. Methods: Intervention assessment tools require an accurate registration of both pre- and postoperative computed tomographies able to handle big deformations. Therefore, a physics-based method is proposed with that purpose. To increase the accuracy both automatically detected internal and surface physical landmarks are incorporated in the registration process. Results: The algorithm has been evaluated in 25 clinical datasets containing RF ablations, resections, and patients with recurrent tumors. The achieved accuracy is 1.2 mm measured as mean internal distance between vessel landmarks and a positive predictive value of 0.95. The quantitative and qualitative results of the outcome validation tool show that in 50% of the cases tumors were only partially covered by the treatment. Conclusion: The use of internal and surface landmarks combined with a physics-based registration method increases the accuracy of the results compared to the accuracy of state of the art methods. An accurate outcome validation tool is important in order to certify that the tumor and its safety margin were fully covered by the treatment. Significance: An accurate outcome validation tool can result in a decrease of the tumor recurrence rate.
Author(s)
Oyarzun Laura, Cristina  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Drechsler, Klaus  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Wesarg, Stefan  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Bale, Reto
Uni-Klinikum Innsbruck
Journal
IEEE Transactions on Biomedical Engineering BME  
DOI
10.1109/TBME.2016.2559945
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • Minimally Invasive Surgery

  • registration

  • liver

  • Lead Topic: Individual Health

  • Research Line: Computer vision (CV)

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