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Blood Detection in IVUS Images for 3D Volume of Lumen Changes Measurement Due to Different Drugs Administration

  • David Rotger
  • Petia Radeva
  • Eduard Fernández-Nofrerías
  • Josepa Mauri
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4673)

Abstract

Lumen volume variations is of great interest by the physicians given it reduces the probability of infarction as it increases. In this paper we present a fast and efficient method to detect the lumen borders in longitudinal cuts of IVUS sequences using an AdaBoost classifier trained with several local features assuring their stability. We propose a criterion for feature selection based on stability leave-one-out cross validation. Results on the segmentation of 18 IVUS pullbacks show that the proposed procedure is fast and robust leading to 90% of time reduction with the same characterization performance.

Keywords

Feature Selection Texture Analysis Local Binary Pattern IVUS Image Medical Image Analysis 
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 2007

Authors and Affiliations

  • David Rotger
    • 1
    • 2
  • Petia Radeva
    • 1
    • 2
  • Eduard Fernández-Nofrerías
    • 3
  • Josepa Mauri
    • 3
  1. 1.Computer Science Department, Autonomous University of BarcelonaSpain
  2. 2.Computer Vision Center, Autonomous University of BarcelonaSpain
  3. 3.University Hospital Germans Trias i PujolSpain

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