Motion estimation in beating heart surgery
Motion estimation in beating heart surgery
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DOI：
10.1109/tbme.2005.855716
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发表时间：
2005-10-01
影响因子：
4.6
通讯作者：
Hirzinger, G
中科院分区：
文献类型：
--
作者：
Ortmaier, T;Gröger, M;Hirzinger, G
与传统的开放手术相比，微创心脏不停跳手术为患者提供了实质性的好处。然而，心脏的运动对外科医生提出了更高的要求。为了支持外科医生，提出了一种先进的机器人手术系统的算法，该系统提供心脏跳动的运动补偿。这意味着测量心脏运动，这可以通过跟踪自然地标来实现。在大多数情况下，所研究的仿射跟踪方案可以简化为允许实时跟踪多个地标的高效块匹配算法。运动参数的傅立叶分析显示有两个主要峰值，分别对应于患者的心率和呼吸频率。在受到干扰或闭塞的情况下，可以通过专门开发的预测方案来提高鲁棒性。局部预测非常适合于单个跟踪离群点的检测。全球预测方案同时考虑了几个地标，并能够弥合更长时间的干扰。由于心脏运动与患者的心电和呼吸压力信号有很强的相关性，这种信息被包含在一种新的稳健的多传感器预测方案中。将预测结果与人工神经网络和线性预测方法的预测结果进行了比较，结果表明所提算法具有较好的性能。
Minimally invasive beating-heart surgery offers substantial benefits for the patient, compared to conventional open surgery. Nevertheless, the motion of the heart poses increased requirements to the surgeon. To support the surgeon, algorithms for an advanced robotic surgery system are proposed, which offer motion compensation of the beating heart. This implies the measurement of heart motion, which can be achieved by tracking natural landmarks. In most cases, the investigated affine tracking scheme can be reduced to an efficient block matching algorithm allowing for realtime tracking of multiple landmarks. Fourier analysis of the motion parameters shows two dominant peaks, which correspond to the heart and respiration rates of the patient.The robustness in case of disturbance or occlusion can be improved by specially developed prediction schemes. Local prediction is well suited for the detection of single tracking outliers. A global prediction scheme takes several landmarks into account simultaneously and is able to bridge longer disturbances. As the heart motion is strongly correlated with the patient's electrocardiogram and respiration pressure signal, this information is included in a novel robust multisensor prediction scheme. Prediction results are compared to those of an artificial neural network and of a linear prediction approach, which shows the superior, performance of the proposed algorithms.