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Improving Patient Specific Neurosurgical Models with Intraoperative Ultrasound and Augmented Reality Visualizations in a Neuronavigation Environment

Part of the Lecture Notes in Computer Science book series (LNIP,volume 9401)

Abstract

We present our work to combine intraoperative ultrasound imaging and augmented reality visualization to improve the use of patient specific models throughout image-guided neurosurgery in the context of tumour resections. Preliminary results in a study of 3 patients demonstrate the successful combination of the two technologies as well as improved accuracy of the patient-specific models throughout the surgery. The augmented reality visualizations enabled the surgeon to accurately visualize the anatomy of interest for an extended period of the intervention. These results demonstrate the potential for these technologies to become useful tools for neurosurgeons to improve patient-specific planning by prolonging the use of reliable neuronavigation.

Keywords

  • Graphic Processing Unit
  • Augmented Reality
  • Registration Error
  • Target Registration Error
  • Brain Shift

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Acknowledgements

We acknowledged funding support from Canadian Institutes of Health Research (MOP-84360 and MOP-111169), the Canadian National Science and Engineering Research Council (238739) and Brain Canada.

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Correspondence to Ian J. Gerard .

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© 2016 Springer International Publishing Switzerland

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Gerard, I.J. et al. (2016). Improving Patient Specific Neurosurgical Models with Intraoperative Ultrasound and Augmented Reality Visualizations in a Neuronavigation Environment. In: , et al. Clinical Image-Based Procedures. Translational Research in Medical Imaging. CLIP 2015. Lecture Notes in Computer Science(), vol 9401. Springer, Cham. https://doi.org/10.1007/978-3-319-31808-0_4

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  • DOI: https://doi.org/10.1007/978-3-319-31808-0_4

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