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

  • Authors:

  • Floris Ernst;Volker Martens;Stefan Schlichting;Armin Beširević;Markus Kleemann;Christoph Koch;Dirk Petersen;Achim Schweikard

  • Affiliations:

  • Institute for Robotics and Cognitive Systems, University of Lübeck;Institute for Robotics and Cognitive Systems, University of Lübeck;Clinic for Surgery, University Hospital Schleswig-Holstein, Lübeck;Clinic for Surgery, University Hospital Schleswig-Holstein, Lübeck;Clinic for Surgery, University Hospital Schleswig-Holstein, Lübeck;Institute for Neuroradiology, University Hospital Schleswig-Holstein, Lübeck;Institute for Neuroradiology, University Hospital Schleswig-Holstein, Lübeck;Institute for Robotics and Cognitive Systems, University of Lübeck

  • Venue:
  • MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

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 ε -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 ε -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.