Guide-Wire Extraction through Perceptual Organization of Local Segments in Fluoroscopic Images
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
Nicolas Honnorat Regis Vaillant Nikos Paragios
Laboratoire MAS, Ecole Centrale Paris, Ch坅tenay-Malabry, France Equipe GALEN, INRIA Saclay-Ile-de-Fr General Electric Healthcare, Buc, France Laboratoire MAS, Ecole Centrale Paris, Chatenay-Malabry, France Equipe GALEN, INRIA Saclay-Ile-de-Fr
国际会议
北京
英文
440–448
2010-09-01（万方平台首次上网日期，不代表论文的发表时间）