Automatic Branching Detection in IVUS Sequences
نویسندگان
چکیده
Atherosclerosis is a vascular pathology a ecting the arterial walls, generally located in speci c vessel sites, such as bifurcations. In this paper, for the rst time, a fully automatic approach for the detection of bifurcations in IVUS pullback sequences is presented. The method identi es the frames and the angular sectors in which a bifurcation is visible. This goal is achieved by applying a classi er to a set of textural features extracted from each image of an IVUS pullback. A comparison between two state-of-the-art classi ers is performed, AdaBoost and Random Forest. A cross-validation scheme is applied in order to evaluate the performances of the approaches. The obtained results are encouraging, showing a sensitivity of 75% and an accuracy of 94% by using the AdaBoost algorithm.
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