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A Deterministic-Statistic Adventitia Detection in IVUS Images

  • Debora Gil
  • Aura Hernandez
  • Antoni Carol
  • Oriol Rodriguez
  • Petia Radeva
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3504)

Abstract

Plaque analysis in IVUS planes needs accurate intima and adventitia models. Large variety in adventitia descriptors difficulties its detection and motivates using a classification strategy for selecting points on the structure. Whatever the set of descriptors used, the selection stage suffers from fake responses due to noise and uncompleted true curves. In order to smooth background noise while strengthening responses, we apply a restricted anisotropic filter that homogenizes grey levels along the image significant structures. Candidate points are extracted by means of a simple semi supervised adaptive classification of the filtered image response to edge and calcium detectors. The final model is obtained by interpolating the former line segments with an anisotropic contour closing technique based on functional extension principles.

Keywords

Feature Space IVUS Image Polar Image Geodesic Active Contour Adaptive Criterion 
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 2005

Authors and Affiliations

  • Debora Gil
    • 1
  • Aura Hernandez
    • 1
  • Antoni Carol
    • 2
  • Oriol Rodriguez
    • 2
  • Petia Radeva
    • 1
  1. 1.Computer Vision CenterUniversitat Autonoma de Barcelona, BellaterraBarcelonaSpain
  2. 2.Hospital Universitari Germans Trias i PujolBadalonaSpain

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