Viewpoint Selection for Angiographic Volume

  • Ming-Yuen Chan
  • Huamin Qu
  • Yingcai Wu
  • Hong Zhou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4291)


In this paper, we present a novel viewpoint selection framework for angiographic volume data. We propose several view descriptors based on typical concerns of clinicians for the view evaluation. Compared with conventional approaches, our method can deliver a more representative global optimal view by sampling at a much higher rate in the view space. Instead of performing analysis on sample views individually, we construct a solution space to estimate the quality of the views. Descriptor values are propagated to the solution space where an efficient searching process can be performed. The best viewpoint can be found by analyzing the accumulated descriptor values in the solution space based on different visualization goals.


Solution Space Good View Optimal View View Selection Direct Volume Rendering 
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 2006

Authors and Affiliations

  • Ming-Yuen Chan
    • 1
  • Huamin Qu
    • 1
  • Yingcai Wu
    • 1
  • Hong Zhou
    • 1
  1. 1.Department of Computer Science and EngineeringThe Hong Kong University of Science and Technology 

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