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Proceedings Paper

The Kinect as an interventional tracking system
Author(s): Xiang Linda Wang; Philipp J. Stolka; Emad Boctor; Gregory Hager; Michael Choti
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Paper Abstract

This work explores the suitability of low-cost sensors for "serious" medical applications, such as tracking of interventional tools in the OR, for simulation, and for education. Although such tracking - i.e. the acquisition of pose data e.g. for ultrasound probes, tissue manipulation tools, needles, but also tissue, bone etc. - is well established, it relies mostly on external devices such as optical or electromagnetic trackers, both of which mandate the use of special markers or sensors attached to each single entity whose pose is to be recorded, and also require their calibration to the tracked entity, i.e. the determination of the geometric relationship between the marker's and the object's intrinsic coordinate frames. The Microsoft Kinect sensor is a recently introduced device for full-body tracking in the gaming market, but it was quickly hacked - due to its wide range of tightly integrated sensors (RGB camera, IR depth and greyscale camera, microphones, accelerometers, and basic actuation) - and used beyond this area. As its field of view and its accuracy are within reasonable usability limits, we describe a medical needle-tracking system for interventional applications based on the Kinect sensor, standard biopsy needles, and no necessary attachments, thus saving both cost and time. Its twin cameras are used as a stereo pair to detect needle-shaped objects, reconstruct their pose in four degrees of freedom, and provide information about the most likely candidate.

Paper Details

Date Published: 17 February 2012
PDF: 6 pages
Proc. SPIE 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling, 83160U (17 February 2012); doi: 10.1117/12.912444
Show Author Affiliations
Xiang Linda Wang, The Johns Hopkins Univ. (United States)
Philipp J. Stolka, The Johns Hopkins Univ. (United States)
Emad Boctor, The Johns Hopkins Univ. (United States)
Johns Hopkins Medical Institutions (United States)
Gregory Hager, The Johns Hopkins Univ. (United States)
Michael Choti, Johns Hopkins Medical Institutions (United States)


Published in SPIE Proceedings Vol. 8316:
Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling
David R. Holmes; Kenneth H. Wong, Editor(s)

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