Technical Section: Visual computing for medical diagnosis and treatment

  • Authors:
  • Jan Klein;Ola Friman;Markus Hadwiger;Bernhard Preim;Felix Ritter;Anna Vilanova;Gabriel Zachmann;Dirk Bartz

  • Affiliations:
  • Fraunhofer MEVIS - Institute for Medical Image Computing, Germany;Fraunhofer MEVIS - Institute for Medical Image Computing, Germany;VRVis Research Center, Vienna, Austria;Otto-von-Guericke-University, Institute for Simulation and Graphics, Germany;Fraunhofer MEVIS - Institute for Medical Image Computing, Germany;Eindhoven University of Technology, Department of Biomedical Engineering, The Netherlands;TU Clausthal, Department of Informatics, Germany;University of Leipzig, ICCAS (Visual Computing), Germany

  • Venue:
  • Computers and Graphics
  • Year:
  • 2009

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Abstract

Diagnostic algorithms and efficient visualization techniques are of major importance for preoperative decisions, intra-operative imaging and image-guided surgery. Complex diagnostic decisions are characterized by a high information flow and fast decisions, requiring efficient and intuitive presentation of complex medical data and precision in the visualization. For intra-operative medical treatment, the pre-operative visualization results of the diagnostic systems have to be transferred to the patient on the operation room table. Via augmented reality, additional information of the hidden regions can be displayed virtually. This state-of-the-art report summarizes visual computing algorithms for medical diagnosis and treatment. After starting with direct volume rendering and tagged volume rendering as general techniques for visualizing anatomical structures, we go into more detail by focusing on the visualization of tissue and vessel structures. Afterwards, algorithms and techniques that are used for medical treatment in the context of image-guided surgery, intra-operative imaging and augmented reality are discussed and reviewed.