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Projective biomechanical depth matching for soft tissue registration in laparoscopic surgery

International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

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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.

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Notes

  1. https://www.sofa-framework.org/.

  2. http://mitk.org.

  3. http://doc.cgal.org/latest/Manual/packages.html#PartMeshing.

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Acknowledgements

The present research was supported by the Klaus Tschira Foundation.

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Authors and Affiliations

  1. Karlsruhe Institute of Technology, Adenauerring 2, Bldg. 50.20, Karlsruhe, Germany

    Daniel Reichard, Dominik Häntsch, Sebastian Bodenstedt, Stefan Suwelack, Rüdiger Dillmann & Stefanie Speidel

  2. Department of General, Abdominal and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany

    Martin Wagner, Hannes Kenngott & Beat Müller-Stich

  3. Junior Group Computer-Assisted Interventions, Division of Medical and Biological Informatics, German Cancer Research Center (DKFZ), Heidelberg, Germany

    Lena Maier-Hein

Authors
  1. Daniel Reichard
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  2. Dominik Häntsch
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  3. Sebastian Bodenstedt
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  4. Stefan Suwelack
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  5. Martin Wagner
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  6. Hannes Kenngott
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  7. Beat Müller-Stich
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  8. Lena Maier-Hein
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  9. Rüdiger Dillmann
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  10. Stefanie Speidel
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Corresponding author

Correspondence to Daniel Reichard.

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The authors declare that they have no conflict of interest.

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All applicable international, national and/or institutional guidelines for the care and use of animals were followed. All procedures performed in studies involving animals were in accordance with the ethical standards of the institution or practice at which the studies were conducted.

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Reichard, D., Häntsch, D., Bodenstedt, S. et al. Projective biomechanical depth matching for soft tissue registration in laparoscopic surgery. Int J CARS 12, 1101–1110 (2017). https://doi.org/10.1007/s11548-017-1613-6

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