Self-adaptive asymmetric on-line boosting for detecting anatomical structures
Proceedings of SPIE(2012)
摘要
In this paper, we propose a self-adaptive, asymmetric on-line boosting (SAAOB) method for detecting anatomical structures in CT pulmonary angiography (CTPA). SAAOB is novel in that it exploits a new asymmetric loss criterion with self-adaptability according to the ratio of exposed positive and negative samples and in that it has an advanced rule to update sample's importance weight taking account of both classification result and sample's label. Our presented method is evaluated by detecting three distinct thoracic structures, the carina, the pulmonary trunk and the aortic arch, in both balanced and imbalanced conditions.
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关键词
Self-Adaptive Asymmetric On-line Boosting (SAAOB),balanced and imbalanced conditions,asymmetric loss criterion,update sample's importance weight,carina,pulmonary trunk,aortic arch
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