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Tissue surface information for intraoperative incision planning and focus adjustment in laser surgery

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Abstract

Purpose

Introducing computational methods to laser surgery are an emerging field. Focusing on endoscopic laser interventions, a novel approach is presented to enhance intraoperative incision planning and laser focusing by means of tissue surface information obtained by stereoscopic vision.

Methods

Tissue surface is estimated with stereo-based methods using nonparametric image transforms. Subsequently, laser-to-camera registration is obtained by ablating a pattern on tissue substitutes and performing a principle component analysis for precise laser axis estimation. Furthermore, a virtual laser view is computed utilizing trifocal transfer. Depth-based laser focus adaptation is integrated into a custom experimental laser setup in order to achieve optimal ablation morphology. Experimental validation is conducted on tissue substitutes and ex vivo animal tissue.

Results

Laser-to-camera registration gives an error between planning and ablation of less than 0.2 mm. As a result, the laser workspace can accurately be highlighted within the live views and incision planning can directly be performed. Experiments related to laser focus adaptation demonstrate that ablation geometry can be kept almost uniform within a depth range of 7.9 mm, whereas cutting quality significantly decreases when the laser is defocused.

Conclusions

An automatic laser focus adjustment on tissue surfaces based on stereoscopic scene information is feasible and has the potential to become an effective methodology for optimal ablation. Laser-to-camera registration facilitates advanced surgical planning for prospective user interfaces and augmented reality extensions.

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Acknowledgments

The research leading to the presented results has received funding from the European Union Seventh Framework Programme FP7/2007–2013 Challenge 2 Cognitive Systems, Interaction, Robotics under grant agreement \(\mu \)RALP - n\(^\mathrm {o}\) 288663.

Conflict of interest

All authors declare that they have no conflict of interest.

Author information

Authors and Affiliations

  1. Institute of Mechatronic Systems, Leibniz Universität Hannover, 30167 , Hanover, Germany

    Andreas Schoob, Dennis Kundrat, Lukas Kleingrothe, Lüder A. Kahrs & Tobias Ortmaier

  2. FEMTO-ST Institute, Université de Franche-Comté/CNRS/ENSMM/UTBM, 25000 , Besançon, France

    Nicolas Andreff

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  1. Andreas Schoob
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  2. Dennis Kundrat
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  6. Tobias Ortmaier
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Correspondence to Andreas Schoob.

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Schoob, A., Kundrat, D., Kleingrothe, L. et al. Tissue surface information for intraoperative incision planning and focus adjustment in laser surgery. Int J CARS 10, 171–181 (2015). https://doi.org/10.1007/s11548-014-1077-x

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  • DOI: https://doi.org/10.1007/s11548-014-1077-x

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