TV-L1-Based 3D Medical Image Registration with the Census Cost Function
TV-L1-Based 3D Medical Image Registration with the Census Cost Function
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DOI：
10.1007/978-3-642-53842-1_13
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发表时间：
2013-10
期刊：
影响因子：
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通讯作者：
S. Hermann;R. Werner
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文献类型：
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作者：
S. Hermann;R. Werner
计算机视觉中的一个最近的趋势是将普查成本函数与TV-L1能量最小化方案结合联合收割机。虽然这种组合在计算机视觉应用中以其鲁棒性能而闻名，但它尚未被引入到3D医学图像配准中。在4D（3D+t）CT图像中解决肺部运动估计，我们建议将普查成本函数纳入3D实现的“基于二元性的方法实时TV-L1光流”的肺部CT配准任务。所提出的算法的性能进行评估的DIR-实验室基准，并比较国家的最先进的方法在这一领域。结果突出了普查成本函数的潜力，特别是准确的肺部运动估计，和一般的3D医学图像配准。
A recent trend in computer vision is to combine the census cost function with a TV-L1energy minimization scheme. Although this combination is known for its robust performance in computer vision applications, it has not been introduced to 3D medical image registration yet. Addressing pulmonary motion estimation in 4D (3D+t) CT images, we propose incorporating the census cost function into a 3D implementation of the ‘duality-based approach for realtime TV-L1optical flow’ for the task of lung CT registration. The performance of the proposed algorithm is evaluated on the DIR-lab benchmark and compared to state-of-the-art approaches in this field. Results highlight the potential of the census cost function for accurate pulmonary motion estimation in particular, and 3D medical image registration in general.