Computer assisted management of disease and surgery: Plato’s cave: A multidimensional, image-guided radiation therapy cross reality platform with advanced surgical planning, simulation, and visualization techniques using (native) dicom patient image studies

Edward Brian Butler, Paul E. Sovelius, Nancy Huynh

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Plato’s CAVE™ (Computer Augmented Virtual Environment) is a presurgical planning, multidimensional “situation clinical platform” designed, developed, and introduced to clinical practice by the Department of Radiation Oncology at Houston Methodist Hospital, located in Houston’s Texas Medical Center. At approximately 500 square feet, Plato’s CAVE was specifically designed to permit a team of physicians to review all available diagnostic images of the patient. The initial clinical focus was on interventions within the domain of surgical oncology/radiation oncology including radiation therapy, reconstructive surgery, and organ transplantation. This advanced clinical visualization process, supported by a novel and creative assemblage of FDA-approved, commercially available diagnostic imaging components, is available for all relevant patient care services within The Methodist Hospital System.

Original languageEnglish (US)
Title of host publicationComputational Surgery and Dual Training: Computing, Robotics and Imaging
PublisherSpringer New York
Pages27-36
Number of pages10
ISBN (Print)9781461486480, 9781461486473
DOIs
StatePublished - Jan 1 2014

Keywords

  • Cave
  • DICOM
  • Dual reality
  • High definition
  • Image-guided therapy
  • Interactive graphics
  • Liver cancer
  • Radiation oncology
  • Stereoscopy
  • Surgical planning
  • Virtual reality
  • Visualization

ASJC Scopus subject areas

  • Engineering(all)

Fingerprint Dive into the research topics of 'Computer assisted management of disease and surgery: Plato’s cave: A multidimensional, image-guided radiation therapy cross reality platform with advanced surgical planning, simulation, and visualization techniques using (native) dicom patient image studies'. Together they form a unique fingerprint.

Cite this