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Intelligent Feature Selection for Model-Based Bone Segmentation in Digital Radiographs

机译:基于模型的数字射线照相骨细分的智能特征选择

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In this paper we propose a method to enhance Active Shape Model based bone segmentation. One major weakness of the classic algorithm is the use of a single dedicated image feature. However to model the variation of image content along the object boundaries it is more suitable to use different features for different regions. We derive an automatic intelligent selection of these features and integrate it into the classic Active Shape Model segmentation. We evaluated the proposed algorithm on the task of delineating bone structures in more than 150 clinical radiographs of the lower extremity and achieve superior accuracy compared to previously published approaches.
机译:在本文中,我们提出了一种增强基于主动形状模型的骨分割的方法。经典算法的一个主要弱点是使用单个专用图像特征。然而,为了模拟沿着物体边界的图像内容的变化,它更适合于使用不同区域的不同特征。我们派生了这些功能的自动智能选择,并将其集成到经典的主动形状​​模型分段中。我们评估了划分骨骼结构任务的提出算法,其在下肢超过150个临床射线照片中,与先前公布的方法相比,实现了卓越的准确性。

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