Abstract
The removal of the prostate is a common treatment option for localized prostate cancer. Robotic prostatectomy uses endoscopic cameras to provide a stereoscopic view of the surgical scene to the surgeon. Often, this surgical scene is difficult to interpret because of variants in anatomy and some critical structures such as the neurovascular bundles alongside the prostate, are affected by variations in size and shape of the prostate. The objective of this article is to develop a real-time stereoscopic video processing framework to improve the perceptibly of the surgical scene, using Eulerian Motion Magnification to exaggerate the subtle pulsatile behavior of the neurovascular bundles. This framework has been validated on both digital phantoms and retrospective analysis of robotic prostatectomy video.
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Acknowledgments
We would like to thank Elvis Chen for his invaluable discussion and editing. Funding for this project was received from Intuitive Surgical, Canadian Institute for Health Research and Canadian Foundation for Innovation. Graduate student funding for Jonathan McLeod was received from the Vanier Canadian Graduate Scholarship program.
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McLeod, A.J., Baxter, J.S.H., Jayarathne, U., Pautler, S., Peters, T.M., Luo, X. (2016). Stereoscopic Motion Magnification in Minimally-Invasive Robotic Prostatectomy. In: Luo, X., Reichl, T., Reiter, A., Mariottini, GL. (eds) Computer-Assisted and Robotic Endoscopy. CARE 2015. Lecture Notes in Computer Science(), vol 9515. Springer, Cham. https://doi.org/10.1007/978-3-319-29965-5_4
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DOI: https://doi.org/10.1007/978-3-319-29965-5_4
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