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Accurate segmentation of ultrasound images using the motion cue

机译:使用运动提示准确分割超声图像

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Accurate segmentation of ultrasound images is desired to measure tissue shapes and sizes. But in some cases, it is difficult to segment ultrasound images purely based on static intensity values. In this paper, we propose a novel segmentation framework by using the motion cue. We integrate a new speckle tracking algorithm into a level set framework to iteratively refine the segmentation and motion estimation at the boundary regions of two different tissues. The balance between local motion contrast of different tissue regions and the smoothness constraint will drive the active contour to the boundaries of different tissues. Experiments on both simulated data and phantom data show that our method has achieved better results than previous methods.
机译:需要超声图像的精确分割以测量组织的形状和大小。但是在某些情况下,仅基于静态强度值很难分割超声图像。在本文中,我们使用运动提示提出了一种新颖的分割框架。我们将一种新的斑点跟踪算法集成到一个水平集框架中,以迭代地改进在两个不同组织的边界区域的分割和运动估计。不同组织区域的局部运动对比度与平滑度约束之间的平衡将驱动活动轮廓到达不同组织的边界。对模拟数据和幻象数据的实验表明,我们的方法比以前的方法取得了更好的结果。

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