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Guide-Wire Extraction through Perceptual Organization of Local Segments in Fluoroscopic Images

  • Nicolas Honnorat
  • Régis Vaillant
  • Nikos Paragios
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6363)

Abstract

Segmentation of surgical devices in fluoroscopic images and in particular of guide-wires is a valuable element during surgery. In cardiac angioplasty, the problem is particularly challenging due to the following reasons: (i) low signal to noise ratio, (ii) the use of 2D images that accumulate information from the whole volume, and (iii) the similarity between the structure of interest and adjacent anatomical structures. In this paper we propose a novel approach to address these challenges, that combines efficiently low-level detection using machine learning techniques, local unsupervised clustering detections and finally high-level perceptual organization of these segments towards its complete reconstruction. The latter handles miss-detections and is based on a local search algorithm. Very promising results were obtained.

Keywords

Local Search False Detection Perceptual Organization Adjacent Anatomical Structure Curvilinear Structure 
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 2010

Authors and Affiliations

  • Nicolas Honnorat
    • 1
    • 2
    • 3
  • Régis Vaillant
    • 3
  • Nikos Paragios
    • 1
    • 2
  1. 1.Laboratoire MASEcole Centrale Paris, Châtenay-MalabryFrance
  2. 2.Equipe GALENINRIA Saclay-Ile-de-FranceOrsayFrance
  3. 3.General Electric HealthcareBucFrance

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