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Real-time motion tracking using 3D ultrasound

机译:使用3D超声波进行实时运动跟踪

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摘要

Three-dimensional (3D) ultrasound is ideally suited to monitor internal organ motion since it offers real-time volumetric imaging without exposing the patient to radiation. We extend a two dimensional (2D) region-tracking algorithm, which was originally used in computer vision, to monitor internal organ motion in 3D. A volume of interest is first selected in an ultrasound volume as a reference. The sum of squared differences is used as the similarity measure to register the reference to each successive volume frame. A transformation model is used to describe the motion and geometric deformation of the reference. The Gauss-Newton method is used to solve the optimization problem. In order to improve the algorithm's efficiency, the Jacobian matrix is decomposed as a product of a time-varying matrix and a constant matrix. The constant matrix is pre-computed to reduce the load of online computation. The algorithm was tested on targets under respiratory motion and cardiac motion. The experimental results show that the transformation model of the algorithm can approximate the geometric distortion of the reference template. With a properly selected reference with rich texture information, the algorithm is sufficiently accurate and robust to follow target motion, and fast enough to be used in real time.
机译:三维(3D)超声非常适合监视内部器官的运动,因为它可以提供实时的体积成像,而不会使患者受到辐射。我们扩展了最初用于计算机视觉的二维(2D)区域跟踪算法,以监控3D内部器官的运动。首先在超声体积中选择感兴趣的体积作为参考。平方差的总和用作相似性度量,以将参考注册到每个连续的体积帧。转换模型用于描述参考的运动和几何变形。高斯-牛顿法用于解决优化问题。为了提高算法的效率,将雅可比矩阵分解为时变矩阵和常数矩阵的乘积。常数矩阵被预先计算以减少在线计算的负担。该算法已在呼吸运动和心脏运动下的目标上进行了测试。实验结果表明,该算法的变换模型可以近似参考模板的几何失真。通过正确选择具有丰富纹理信息的参考,该算法具有足够的准确性和鲁棒性,可以跟随目标运动,并且足够快,可以实时使用。

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