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Treatment Planning for Image-Guided Robotic Radiosurgery

  • Rhea Tombropoulos
  • Achim Schweikard
  • Jean-Claude Latombe
  • John R. Adler
Part of the Lecture Notes in Computer Science book series (LNCS, volume 905)

Abstract

Radiosurgery is a non-invasive procedure that uses focused beams of radiation to destroy brain tumors. Treatment planning for radiosurgery involves determining a series of beam configurations that will destroy the tumor without damaging healthy tissue in the brain, particularly critical structures. A new image-guided robotic radiosurgical system has been developed at Stanford University in a joint project with Accuray, Inc. It has been in clinical use at Stanford since July, 1994, and thus far three patients have been treated with it. This system provides much more flexibility for treatment planning than do traditional radiosurgical systems. In order to take full advantage of this added flexibility, we have developed automatic methods for treatment planning. Our planner enables a surgeon to specify constraints interactively on the distribution of dose delivered and then to find a set of beam configurations that will satisfy these constraints. We provide a detailed description of our treatment planning algorithms and summarize our first experiences using the system in a clinical setting.

Keywords

Dose Distribution Target Point Beam Configuration Computer Assist Surgery Healthy Brain Tissue 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Rhea Tombropoulos
    • 1
    • 2
  • Achim Schweikard
    • 2
    • 3
  • Jean-Claude Latombe
    • 2
  • John R. Adler
    • 3
  1. 1.Section on Medical InformaticsStanford UniversityStanfordUSA
  2. 2.Department of Computer Science Robotics LaboratoryStanford UniversityStanfordUSA
  3. 3.Department of NeurosurgeryStanford UniversityStanfordUSA

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