Robust guidewire segmentation through boosting, clustering and linear programming

Nicolas Honnorat, Ŕegis Vaillant, Nikos Paragios

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Fluroscopic imaging provides means to assess the motion of the internal structures and therefore is of great use during surgery. In this paper we propose a novel approach for the segmentation of curvilinear structures in these images. The main challenge to be addressed is the lack of visual support due to the low SNR where traditional edgebased methods fail. Our approach combines machine learning techniques, unsupervised clustering and linear programming. In particular, numerous invariant to position/rotation classifiers are combined to detect candidate pixels of curvilinear structure. These candidates are grouped into consistent geometric segments through the use of a state-of-the art unsupervised clustering algorithm. The complete curvilinear structure is obtained through an ordering of these segments using the elastica model in a linear programming framework. Very promising results were obtained on guide wire segmentation in fluoroscopic images.

Original languageEnglish (US)
Title of host publication2010 7th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI 2010 - Proceedings
Pages924-927
Number of pages4
DOIs
StatePublished - 2010
Externally publishedYes
Event7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Rotterdam, Netherlands
Duration: Apr 14 2010Apr 17 2010

Publication series

Name2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings

Other

Other7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010
Country/TerritoryNetherlands
CityRotterdam
Period4/14/104/17/10

Keywords

  • Boosting
  • Clustering
  • Fluoroscopic images
  • Guide wire
  • Linear programming
  • Linear structures
  • Steerable filters

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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