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JACIII Vol.20 No.5 pp. 735-742
doi: 10.20965/jaciii.2016.p0735
(2016)

Paper:

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Real-Time 3D Visualization and Navigation Using Fiber-Based Endoscopic System for Arthroscopic Surgery

Zhongjie Long*,**, Kouki Nagamune*,***, Ryosuke Kuroda***, and Masahiro Kurosaka***

*Department of Human and Artificial Intelligent Systems, University of Fukui
Fukui 910-8507, Japan

**Beijing Information Science and Technology University
Beijing 100192, China

***Department of Orthopaedic Surgery, Kobe University
Kobe 650-0017, Japan

Received:
February 9, 2016
Accepted:
June 9, 2016
Published:
September 20, 2016
Creative Commons License
Keywords:
3D navigation, visualization, knee joint, arthroscopy, minimally invasive surgery
Abstract
Three-dimensional (3D) navigation using a computer-assisted technique is being increasingly performed in minimally invasive surgical procedures because it can provide stereoscopic information regarding the operating field to the surgeon. In this paper, the development of a real-time arthroscopic system utilizing an endoscopic camera and optical fiber to navigate a normal vector for a reconstructed knee joint surface is described. A specific navigation approach suitable for use in a rendered surface was presented in extenso. A small-sized endoscopic tube was utilized arthroscopically on a cadaveric knee joint to show the potential application of the developed system. Experimental results of underwater navigation on a synthetic knee joint showed that our system allows for a higher accuracy than a freehand technique. The mean angle of navigation for the proposed technique is 9.5circ (range, 5circ to 17circ; SD, 2.86circ) versus 14.8circ (range, 6circ to 26circ; SD, 7.53circ) and 12.6circ (range, 4circ to 17circ; SD, 3.98circ) for two sites using a freehand technique.
Cite this article as:
Z. Long, K. Nagamune, R. Kuroda, and M. Kurosaka, “Real-Time 3D Visualization and Navigation Using Fiber-Based Endoscopic System for Arthroscopic Surgery,” J. Adv. Comput. Intell. Intell. Inform., Vol.20 No.5, pp. 735-742, 2016.
Data files:
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