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Open-Source Development of a Low-Cost Stereo-Endoscopy System for Natural Orifice Transluminal Endoscopic Surgery

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Computer Vision Systems (ICVS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10528))

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Abstract

As a minimally invasive procedure, Natural Orifice Transluminal Endoscopic Surgery (NOTES) offers many significant benefits over traditional open surgery, including reduced risks of post-operative complication and a faster recovery rate. However, one major challenge commonly faced when performing such procedures is the lack of depth perception provided by standard monocular endoscopes, which can in turn pose a limitation on the effectiveness of such endoscopic surgery. To overcome this undesirable lack of depth perception during endoscopic imaging, stereoscopic vision can be introduced into current endoscopy technology to assist surgeons in performing safer and faster operations with better depth judgement. While there is already a vast range of highly advanced stereo-endoscopy systems commercially available in the market, practical implementation of these systems still remains to be largely minimal as a result of their high costs. This paper presents our approach for integrating affordability with functionality, through the development of a simple, low-cost stereo-endoscopy system. Constructed using commonly off-the-shelf materials, the system runs in real time to present stereoscopic images acquired from the stereo-endoscope cameras into the surgeon’s eyes simultaneously, thereby equipping the surgeon with binocular vision for depth perception during endoscopic surgery.

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Acknowledgements

This work is supported by the Singapore Academic Research Fund under Grant R-397-000-227-112, NUSRI China Jiangsu Provincial Grant BK20150386 & BE2016077 awarded to Dr. Hongliang Ren.

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Correspondence to Hongliang Ren .

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Koh, J.X., Ren, H. (2017). Open-Source Development of a Low-Cost Stereo-Endoscopy System for Natural Orifice Transluminal Endoscopic Surgery. In: Liu, M., Chen, H., Vincze, M. (eds) Computer Vision Systems. ICVS 2017. Lecture Notes in Computer Science(), vol 10528. Springer, Cham. https://doi.org/10.1007/978-3-319-68345-4_32

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  • DOI: https://doi.org/10.1007/978-3-319-68345-4_32

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  • Print ISBN: 978-3-319-68344-7

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