Daniel Reichard1, Dominik Häntsch2, Sebastian Bodenstedt2, Stefan Suwelack2, Martin Wagner3, Hannes Kenngott3, Beat Müller-Stich3, Lena Maier-Hein4, Rüdiger Dillmann2, Stefanie Speidel2. 1. Karlsruhe Institute of Technology, Adenauerring 2, Bldg. 50.20, Karlsruhe, Germany. daniel.reichard@kit.edu. 2. Karlsruhe Institute of Technology, Adenauerring 2, Bldg. 50.20, Karlsruhe, Germany. 3. Department of General, Abdominal and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany. 4. Junior Group Computer-Assisted Interventions, Division of Medical and Biological Informatics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
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.
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.
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