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

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.
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Communication dans un congrès
13th International Conference on Medical Image Computing and Computer Assisted Intervention - MICCAI 2010, Sep 2010, Beijing, China. 6363, pp.440-448, 2010, 〈10.1007/978-3-642-15711-0_55〉
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Contributeur : Vivien Fécamp <>
Soumis le : vendredi 30 août 2013 - 13:34:35
Dernière modification le : mardi 5 février 2019 - 13:52:14

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Nicolas Honnorat, Régis Vaillant, Nikos Paragios. Guide-Wire Extraction through Perceptual Organization of Local Segments in Fluoroscopic Images. 13th International Conference on Medical Image Computing and Computer Assisted Intervention - MICCAI 2010, Sep 2010, Beijing, China. 6363, pp.440-448, 2010, 〈10.1007/978-3-642-15711-0_55〉. 〈hal-00856049〉

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