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Proceedings Paper

Feasibility of human/robot cooperation in image-directed radiation oncology
Author(s): Scott A. Ameduri; Wyatt S. Newman; Martin S. Weinhous; Greg D. Glosser; Roger Macklis
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Paper Abstract

Image-directed radiation therapy potentially offers significant improvement over current open-loop radiotherapy techniques. Utilizing real-time imaging of tumors, it may be possible to direct a treatment beam to achieve better localization of radiation dose. Since real-time imaging offers relatively poor fidelity, automated analysis of images is formidable. However, experienced physicians may take advantage of visual cues and knowledge of how cancer spreads to infer the location of tumors in partially occluded or otherwise ambiguous scenes. At the Cleveland Clinic, an image-directed radiation treatment system, consisting of a relatively compact linear accelerator manipulated by a 6 degree-of-freedom robot, is in use for treatment of brain tumors. This same system could be applied to teleoperated radiation treatment of non-stationary tumors. To evaluate the prospects for operator-interactive, image-directed therapy, a simulator was constructed to determine the effectiveness of emulated human-in-the-loop treatments. Early performance results based on video recordings of actual lung tumors show that image-directed treatment can offer significant improvements over current practice, motivating development of teleoperated treatment systems.

Paper Details

Date Published: 18 December 1998
PDF: 10 pages
Proc. SPIE 3524, Telemanipulator and Telepresence Technologies V, (18 December 1998); doi: 10.1117/12.333693
Show Author Affiliations
Scott A. Ameduri, Case Western Reserve Univ. (United States)
Wyatt S. Newman, Case Western Reserve Univ. (United States)
Martin S. Weinhous, Cleveland Clinic Foundation (United States)
Greg D. Glosser, Cleveland Clinic Foundation (United States)
Roger Macklis, Cleveland Clinic Foundation (United States)

Published in SPIE Proceedings Vol. 3524:
Telemanipulator and Telepresence Technologies V
Matthew R. Stein, Editor(s)

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