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Eigenmotion-Based Detection of Intestinal Contractions

  • Laura Igual
  • Santi Seguí
  • Jordi Vitrià
  • Fernando Azpiroz
  • Petia Radeva
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4673)

Abstract

Intestinal contractions are one of the main features for analyzing intestinal motility and detecting different gastrointestinal pathologies. In this paper we propose Eigenmotion-based Contraction Detection (ECD), a novel approach for automatic annotation of intestinal contractions of video capsule endoscopy. Our approach extracts the main motion information of a set of contraction sequences in form of eigenmotions using Principal Component Analysis. Then, it uses a selection of them to represent the high dimension motion data. Finally, this contraction characterization is used to classify the contraction sequences by means of machine learning techniques. The experimental results show that motion information is useful in the contraction detection. Moreover, the proposed automatic method is essential to speed up the costly examination of the video capsule endoscopy.

Keywords

Video Sequence Motion Estimation Independent Component Analysis Intestinal Motility Relevance Vector Machine 
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

  • Laura Igual
    • 1
  • Santi Seguí
    • 1
  • Jordi Vitrià
    • 1
  • Fernando Azpiroz
    • 2
  • Petia Radeva
    • 1
  1. 1.Computer Vision Center and Universidad Autónoma de Barcelona, BellaterraSpain
  2. 2.Hospital de Vall d’Hebron, BarcelonaSpain

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