High Accuracy Optical Flow for 3D Medical Image Registration Using the Census Cost Function
High Accuracy Optical Flow for 3D Medical Image Registration Using the Census Cost Function
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DOI：
10.1007/978-3-642-53842-1_3
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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
中科院分区：
文献类型：
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作者：
S. Hermann;R. Werner
2004 年，布罗克斯等人。描述了如何最小化密集二维光流估计的能量函数，以强制强度和梯度恒定性。本文提出了他们的方法的一种新颖变体，其中在数据项中使用普查成本函数而不是绝对强度差。该算法应用于 3D 计算机断层扫描 (CT) 图像序列中的肺部运动估计任务。性能评估基于 DIR-lab 肺部 CT 配准基准数据。结果表明，所提出的算法在配准精度和运行时间方面可以与当前最先进的方法相媲美。
In 2004, Brox et al. described how to minimize an energy functional for dense 2D optical flow estimation that enforces both intensity and gradient constancy.This paper presents a novel variant of their method, in which the census cost function is utilized in the data term instead of absolute intensity differences. The algorithm is applied to the task of pulmonary motion estimation in 3D computed tomography (CT) image sequences. The performance evaluation is based on DIR-lab benchmark data for lung CT registration. Results show that the presented algorithm can compete with current state-of-the-art methods in regards to both registration accuracy and run-time.