Technical Briefs

A Low-Cost Computer Vision Based Approach for Tracking Surgical Robotic Tools

[+] Author and Article Information
Timothy M. Kowalewski

Department of Mechanical Engineering,
University of Minnesota

Manuscript received March 15, 2013; final manuscript received April 26, 2013; published online July 3, 2013. Assoc. Editor: Arthur G. Erdman.

J. Med. Devices 7(3), 030917 (Jul 03, 2013) (2 pages) Paper No: MED-13-1072; doi: 10.1115/1.4024497 History: Received March 15, 2013; Revised April 26, 2013

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Satava, R., and Smith, R., 2012, “Fundamentals of Robotic Surgery: Outcomes Measures and Curriculum Development,” Society of Laparoendoscopic Surgeons, pp. 1–2.
Chmarra, M. K., Grimbergen, C. A., and Dankelman, J., 2007, “Systems for Tracking Minimally Invasive Surgical Instruments,” Minimally Invasive Therapy, pp. 328–340. [CrossRef]
Kowalewski, T. M., 2012, “Real-Time Quantitative Assessment of Surgical Skill,” PhD dissertation, University of Washington.
WillowGarage, and Bradski, G., 2012, “Open Source Computer Vision” from http://opencv.willowgarage.com/wiki/
Digia Plc, 2012, “Qt Developer Network” from http://qt- project.org/
Laganiere, R., 2011, OpenCV2 Computer Vision Application Programming Handbook, 1st ed., Packt Publishing, Birmingham, UK, Chap. 9.


Grahic Jump Location
Fig. 4

Stereo matching correctly extracts relative depth of da Vinci tools from background

Grahic Jump Location
Fig. 1

Software component and thread mapping




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