Feasibility of human/robot cooperation in image-directed radiation oncology

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.

[1]  Yan Zhu,et al.  Computerized tumor boundary detection using a Hopfield neural network , 1997, IEEE Transactions on Medical Imaging.

[2]  C. Chen,et al.  Medical Image Segmentation By A Constraint Satisfaction Neural Network , 1990, 1990 IEEE Nuclear Science Symposium Conference Record.

[3]  Matthew T. Freedman,et al.  Artificial convolution neural network techniques and applications for lung nodule detection , 1995, IEEE Trans. Medical Imaging.

[4]  Hemant D. Tagare Deformable 2-D template matching using orthogonal curves , 1997, IEEE Transactions on Medical Imaging.