Feasibility and analysis of CNN-based candidate beam generation for robotic radiosurgery.

Journal: Medical physics
Published Date:

Abstract

PURPOSE: Robotic radiosurgery offers the flexibility of a robotic arm to enable high conformity to the target and a steep dose gradient. However, treatment planning becomes a computationally challenging task as the search space for potential beam directions for dose delivery is arbitrarily large. We propose an approach based on deep learning to improve the search for treatment beams.

Authors

  • Stefan Gerlach
    Institute of Medical Technology, Hamburg University of Technology, Hamburg, Germany.
  • Christoph Fürweger
    Europäisches Cyberknife Zentrum München-Großhadern, Munich, Germany.
  • Theresa Hofmann
    Europäisches Cyberknife Zentrum München-Großhadern, Munich, 81377, Germany.
  • Alexander Schlaefer
    Institute of Medical Technology, Hamburg University of Technology, Hamburg, Germany. schlaefer@tuhh.de.