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In robotic radiosurgery, the compensation of motion of internal organs is vital. This is currently done in two phases: an external surrogate signal (usually active optical markers placed on the patient's chest) is recorded and subsequently correlated to an internal motion signal obtained using stereoscopic X-ray imaging. This internal signal is sampled very infrequently to minimise the patient's exposure to radiation. We have investigated the correlation of the external signal to the motion of the liver in a porcine study using epsilon-support vector regression. IR LEDs were placed on the swines' chest. Gold fiducials were placed in the swines' livers and were recorded using a two-plane X-ray system. The results show that a very good correlation model can be built using epsilon-SVR, in this test clearly outperforming traditional polynomial models by at least 45 and as much as 74%. Using multiple markers simultaneously can increase the new model's accuracy.

Correlating Chest Surface Motion to Motion of the Liver Using ε-SVR – A Porcine Study