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Pyramid Histograms of Motion Context with Application to Angiogram Video Classification

  • Fei Wang
  • Yong Zhang
  • David Beymer
  • Hayit Greenspan
  • Tanveer Syeda-Mahmood
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6666)

Abstract

Due to poor image quality as well as the difficulty of modeling the non-rigid heart motion, motion information has rarely been used in the past for angiogram analysis. In this paper we propose a new motion feature for the purpose of classifying angiogram videos according to their viewpoints. Specifically, local motion content of the video around the anatomical structures cardiac vessels is represented using the so-called “motion context”, a motion histogram representation in polar coordinates within a local patch. The global motion layout is captured as pyramid histograms of the motion context (PHMC) in a manner similar to that proposed by the Spatial Pyramid Kernel [1]. The PHMC is a robust representation of the motion features in a video sequence. Through experiments on a large database of angiograms obtained from both diseased and control subjects, we show that our technique consistently outperforms state-of-the-art methods in the angiogram classification test.

Keywords

Right Coronary Artery Left Coronary Artery Shape Context Coronary Artery Tree Vessel Centerline 
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 2011

Authors and Affiliations

  • Fei Wang
    • 1
  • Yong Zhang
    • 1
  • David Beymer
    • 1
  • Hayit Greenspan
    • 1
    • 2
  • Tanveer Syeda-Mahmood
    • 1
  1. 1.IBM Almaden Research CenterSan JoseUSA
  2. 2.Biomedical Engineering DeptTel-Aviv UniversityIsrael

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