Projective biomechanical depth matching for soft tissue registration in laparoscopic surgery

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Daniel Reichard - , Karlsruher Institut für Technologie (Autor:in)
  • Dominik Häntsch - , Karlsruher Institut für Technologie (Autor:in)
  • Sebastian Bodenstedt - , Karlsruher Institut für Technologie (Autor:in)
  • Stefan Suwelack - , Karlsruher Institut für Technologie (Autor:in)
  • Martin Wagner - , Universität Heidelberg (Autor:in)
  • Hannes Kenngott - , Universität Heidelberg (Autor:in)
  • Beat Müller-Stich - , Universität Heidelberg (Autor:in)
  • Lena Maier-Hein - , Deutsches Krebsforschungszentrum (DKFZ) (Autor:in)
  • Rüdiger Dillmann - , Karlsruher Institut für Technologie (Autor:in)
  • Stefanie Speidel - , Karlsruher Institut für Technologie (Autor:in)

Abstract

Purpose: A key component of computer- assisted surgery systems is the accurate and robust registration of preoperative planning data with intraoperative sensor data. In laparoscopic surgery, this image-based registration remains challenging due to soft tissue deformations. This paper presents a novel approach for biomechanical soft tissue registration of preoperative CT data with stereo endoscopic image data. Methods: The proposed method consists of two registrations steps. First, we use a 3D surface mosaic from partial surfaces reconstructed from stereo endoscopic images to initially align the biomechanical model with the intraoperative position and shape of the organ. After this initialization, the biomechanical model is projected onto newly captured surfaces, resulting in displacement boundary conditions, which in turn are used to update the biomechanical model. Results: The method is evaluated in silico, using a human liver model, and in vivo, using porcine data. The quantitative in silico data shows a stable behaviour of the biomechanical model and root-mean-square deviation of volume vertices of under 3 mm with adjusted biomechanical parameters. Conclusion: This work contributes a fully automatic featureless non-rigid registration approach. The results of the in silico and in vivo experiments suggest that our method is able to handle dynamic deformations during surgery. Additional experiments, especially regarding human tissue behaviour, are an important next step towards clinical applications.

Details

OriginalspracheEnglisch
Seiten (von - bis)1101-1110
Seitenumfang10
FachzeitschriftInternational journal of computer assisted radiology and surgery
Jahrgang12
Ausgabenummer7
PublikationsstatusVeröffentlicht - 1 Juli 2017
Peer-Review-StatusJa
Extern publiziertJa

Externe IDs

PubMed 28550405
ORCID /0000-0002-4590-1908/work/163294019

Schlagworte

Schlagwörter

  • Biomechanical registration, Endoscopic vision, Intraoperative registration, Minimally invasive procedures