P6D-2 Ultrasound Bone Segmentation Using Dynamic Programming

P. Foroughi, E. Boctor, M. Swartz, R. H. Taylor, G. Fichtinger
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引用次数: 76

Abstract

Segmentation of bone surface in ultrasound images has numerous applications in computer aided orthopedic surgery. A robust bone surface extraction technique for ultrasound images can be used to non-invasively probe the bone surface. In this work, we present early results with an intuitive and computationally inexpensive bone segmentation approach. The prior knowledge about the appearance of bone in ultrasound images is exploited toward achieving robust and fast bone segmentation. Continuity and smoothness of the bone surface are incorporated in a cost function, which is globally minimized using dynamic programming. The performance of this method is evaluated on ultrasound images collected from two male cadavers. The images are segmented in about half a second making the algorithm suitable for real-time applications. Comparison between manual and automatic segmentation shows an average accuracy of less than 3 pixels (0.3 mm).
基于动态规划的P6D-2超声骨分割
超声图像中骨表面的分割在计算机辅助骨科手术中有着广泛的应用。一种鲁棒的骨表面超声图像提取技术可用于无创探测骨表面。在这项工作中,我们提出了一种直观且计算成本低廉的骨分割方法的早期结果。利用超声图像中骨骼外观的先验知识来实现鲁棒和快速的骨骼分割。将骨表面的连续性和平滑性纳入成本函数,并利用动态规划实现全局最小化。在两具男性尸体的超声图像上对该方法的性能进行了评价。该算法在半秒左右的时间内完成图像分割,适合于实时应用。手动分割和自动分割的比较表明,平均精度小于3像素(0.3毫米)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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