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Localization of Bone Surfaces from Ultrasound Data Using Local Phase Information and Signal Transmission Maps

机译:使用局部相位信息和信号传输图从超声数据中对骨表面进行定位

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摘要

Low signal-to-noise ratio, imaging artifacts and bone boundaries appearing several millimeters in thickness have hampered the success of ultrasound (US) guided computer assisted orthopedic surgery procedures. In this paper we propose a robust and accurate bone localization method. The proposed approach is based on the enhancement of bone surfaces using the combination of three different local image phase features. The extracted local phase image features are used as an input to an L_1 norm-based contextual regularization method for the enhancement of bone shadow regions. During the final stage the enhanced bone features and shadow region information is combined into a dynamic programming solution for the localization of the bone surface data. Qualitative and quantitative validation was performed on 150 in vivo US scans obtained from seven subjects by scanning femur, knee, distal radius and vertebrae bones. Validation against expert segmentation achieved a mean surface localization error of 0.26 mm a 67% improvement over state of the art.
机译:低信噪比,成像伪影和出现在厚度上几毫米的骨骼边界阻碍了超声(US)引导的计算机辅助骨科手术程序的成功。在本文中,我们提出了一种鲁棒且准确的骨骼定位方法。所提出的方法基于使用三个不同局部图像相位特征的组合来增强骨骼表面。提取的局部相位图像特征用作基于L_1规范的上下文正则化方法的输入,用于增强骨影区域。在最后阶段,将增强的骨骼特征和阴影区域信息组合到用于骨骼表面数据定位的动态编程解决方案中。定性和定量验证是通过扫描股骨,膝盖,distal骨远端和椎骨对七名受试者进行的150次体内US扫描进行的。针对专家分割的验证实现了0.26 mm的平均表面定位误差,与现有技术相比提高了67%。

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