Abstract
Augmented reality for soft tissue laparoscopic surgery is a growing topic of interest in the medical community and has potential application in intra-operative planning and image guidance. Delivery of such systems to the operating room remains complex with theoretical challenges related to tissue deformation and the practical limitations of imaging equipment. Current research in this area generally only solves part of the registration pipeline or relies on fiducials, manual model alignment or assumes that tissue is static. This paper proposes a novel augmented reality framework for intra-operative planning: the approach co-registers pre-operative CT with stereo laparoscopic images using cone beam CT and fluoroscopy as bridging modalities. It does not require fiducials or manual alignment and compensates for tissue deformation from insufflation and respiration while allowing the laparoscope to be navigated. The paper’s theoretical and practical contributions are validated using simulated, phantom, ex vivo, in vivo and non medical data.
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Keywords
- Augmented Reality
- Iterative Close Point
- Laparoscopic Partial Nephrectomy
- Tissue Deformation
- Target Registration Error
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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Mountney, P., Fallert, J., Nicolau, S., Soler, L., Mewes, P.W. (2014). An Augmented Reality Framework for Soft Tissue Surgery. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014. MICCAI 2014. Lecture Notes in Computer Science, vol 8673. Springer, Cham. https://doi.org/10.1007/978-3-319-10404-1_53
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DOI: https://doi.org/10.1007/978-3-319-10404-1_53
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