Hu Mingxing, Penney Graeme, Rueckert Daniel, Edwards Philip, Figl Michael, Pratt Philip, Hawkes David
Centre for Medical Image Computing, University College London.
Med Image Comput Comput Assist Interv. 2008;11(Pt 1):720-8. doi: 10.1007/978-3-540-85988-8_86.
Recently, much attention has been focused on heart motion analysis for minimally invasive beating-heart surgery. Unfortunately existing techniques usually require the camera(s) to be fixed during the motion analysis, which can restrict its usefulness during surgery. In this paper we present a novel method for heart motion analysis using geometric constraint, which can estimate the motion from a moving camera and employ multiple image features to improve robustness to noise. Our approach combines the benefits of geometry estimation for obtaining an accurate and robust solution with the proper treatment of respiratory motion. The proposed method can be applied to not only beating heart surgery, but also to other procedures involving periodic organ motion, such as lung and liver.
最近，微创心脏跳动手术中的心脏运动分析受到了广泛关注。不幸的是，现有技术在运动分析过程中通常要求摄像机固定，这可能会限制其在手术中的实用性。在本文中，我们提出了一种使用几何约束进行心脏运动分析的新方法，该方法可以从移动的摄像机估计运动，并利用多个图像特征来提高对噪声的鲁棒性。我们的方法结合了几何估计的优点，以获得准确而稳健的解决方案，并对呼吸运动进行适当处理。所提出的方法不仅可以应用于心脏跳动手术，还可以应用于其他涉及周期性器官运动的手术，如肺部和肝脏手术。
