title: Physics-based shape matching for intraoperative image guidance.
abstract: OBJECTIVE
  Soft-tissue deformations can severely degrade the validity of preoperative planning data during computer assisted interventions. Intraoperative imaging such as stereo endoscopic, time-of-flight or, laser range scanner data can be used to compensate these movements. In this context, the intraoperative surface has to be matched to the preoperative model. The shape matching is especially challenging in the intraoperative setting due to noisy sensor data, only partially visible surfaces, ambiguous shape descriptors, and real-time requirements.
  
  
  METHODS
  A novel physics-based shape matching (PBSM) approach to register intraoperatively acquired surface meshes to preoperative planning data is proposed. The key idea of the method is to describe the nonrigid registration process as an electrostatic-elastic problem, where an elastic body (preoperative model) that is electrically charged slides into an oppositely charged rigid shape (intraoperative surface). It is shown that the corresponding energy functional can be efficiently solved using the finite element (FE) method. It is also demonstrated how PBSM can be combined with rigid registration schemes for robust nonrigid registration of arbitrarily aligned surfaces. Furthermore, it is shown how the approach can be combined with landmark based methods and outline its application to image guidance in laparoscopic interventions.
  
  
  RESULTS
  A profound analysis of the PBSM scheme based on in silico and phantom data is presented. Simulation studies on several liver models show that the approach is robust to the initial rigid registration and to parameter variations. The studies also reveal that the method achieves submillimeter registration accuracy (mean error between 0.32 and 0.46 mm). An unoptimized, single core implementation of the approach achieves near real-time performance (2 TPS, 7-19 s total registration time). It outperforms established methods in terms of speed and accuracy. Furthermore, it is shown that the method is able to accurately match partial surfaces. Finally, a phantom experiment demonstrates how the method can be combined with stereo endoscopic imaging to provide nonrigid registration during laparoscopic interventions.
  
  
  CONCLUSIONS
  The PBSM approach for surface matching is fast, robust, and accurate. As the technique is based on a preoperative volumetric FE model, it naturally recovers the position of volumetric structures (e.g., tumors and vessels). It cannot only be used to recover soft-tissue deformations from intraoperative surface models but can also be combined with landmark data from volumetric imaging. In addition to applications in laparoscopic surgery, the method might prove useful in other areas that require soft-tissue registration from sparse intraoperative sensor data (e.g., radiation therapy).
authors.affiliation: Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology, Adenauerring 2, Karlsruhe 76131, Germany.
authors.forename: Stefan
authors.initials: S
authors.lastname: Suwelack
authors.affiliation: Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology, Adenauerring 2, Karlsruhe 76131, Germany.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Röhl
authors.affiliation: Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology, Adenauerring 2, Karlsruhe 76131, Germany.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Bodenstedt
authors.affiliation: Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology, Adenauerring 2, Karlsruhe 76131, Germany.
authors.forename: Daniel
authors.initials: D
authors.lastname: Reichard
authors.affiliation: Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology, Adenauerring 2, Karlsruhe 76131, Germany.
authors.forename: Rüdiger
authors.initials: R
authors.lastname: Dillmann
authors.affiliation: Computer-assisted Interventions, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg 69120, Germany.
authors.forename: Thiago
authors.initials: T
authors.lastname: dos Santos
authors.affiliation: Computer-assisted Interventions, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg 69120, Germany.
authors.forename: Lena
authors.initials: L
authors.lastname: Maier-Hein
authors.affiliation: General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Im Neuenheimer Feld 110, Heidelberg 69120, Germany.
authors.forename: Martin
authors.initials: M
authors.lastname: Wagner
authors.affiliation: General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Im Neuenheimer Feld 110, Heidelberg 69120, Germany.
authors.forename: Josephine
authors.initials: J
authors.lastname: Wünscher
authors.affiliation: General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Im Neuenheimer Feld 110, Heidelberg 69120, Germany.
authors.forename: Hannes
authors.initials: H
authors.lastname: Kenngott
authors.affiliation: General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Im Neuenheimer Feld 110, Heidelberg 69120, Germany.
authors.forename: Beat P
authors.initials: BP
authors.lastname: Müller
authors.affiliation: Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology, Adenauerring 2, Karlsruhe 76131, Germany.
authors.forename: Stefanie
authors.initials: S
authors.lastname: Speidel
mesh_terms: D000465:Algorithms; D001696:Biomechanical Phenomena; D003198:Computer Simulation; D004548:Elasticity; D020342:Finite Element Analysis; D007432:Intraoperative Period; D019047:Phantoms, Imaging; D055585:Physical Phenomena; D055672:Static Electricity; D025321:Surgery, Computer-Assisted / Q000379:methods*