膝关节负重锥形梁CT运动补偿的惯性测量
Inertial Measurements for Motion Compensation in Weight-bearing Cone-beam CT of the Knee
摘要：
膝关节负重锥形束计算机断层扫描（CT）过程中的不自主运动会导致重建体积中的伪影，使其无法用于临床诊断。目前，应用基于图像或基于标记的方法来校正这种运动，但通常需要长的执行或准备时间。我们建议附加一个惯性测量单元（IMU）包含一个加速度计和一个陀螺仪的对象的腿，以测量在扫描过程中的运动和纠正it. To验证这种方法，我们提出了一个模拟研究，使用实际运动测量的光学三维跟踪系统。通过这种运动，XCAT数值膝关节体模在模拟CT扫描期间非刚性变形，产生运动破坏投影。使用相同的跟踪运动对生物力学模型进行动画处理，以生成放置在膝盖下方的IMU的测量结果。在我们提出的多阶段算法中，这些信号被转换到CT扫描的全局坐标系中，并在重建过程中用于运动补偿。我们提出的方法可以有效地减少重建体积中的运动伪影。与运动破坏的情况相比，相对于无运动的情况，平均结构相似性指数和均方根误差分别提高了13-21%和68- 70%。这些结果在定性和定量上与我们比较的最先进的基于标记的方法相当。所提出的研究表明，这种新的方法的可行性，并产生有前途的结果对一个纯粹的基于IMU的运动补偿在C型臂CT。
英文摘要：
Involuntary motion during weight-bearing cone-beam computed tomography (CT) scans of the knee causes artifacts in the reconstructed volumes making them unusable for clinical diagnosis. Currently, image-based or marker-based methods are applied to correct for this motion, but often require long execution or preparation times. We propose to attach an inertial measurement unit (IMU) containing an accelerometer and a gyroscope to the leg of the subject in order to measure the motion during the scan and correct for it. To validate this approach, we present a simulation study using real motion measured with an optical 3D tracking system. With this motion, an XCAT numerical knee phantom is non-rigidly deformed during a simulated CT scan creating motion corrupted projections. A biomechanical model is animated with the same tracked motion in order to generate measurements of an IMU placed below the knee. In our proposed multi-stage algorithm, these signals are transformed to the global coordinate system of the CT scan and applied for motion compensation during reconstruction. Our proposed approach can effectively reduce motion artifacts in the reconstructed volumes. Compared to the motion corrupted case, the average structural similarity index and root mean squared error with respect to the no-motion case improved by 13-21% and 68-70%, respectively. These results are qualitatively and quantitatively on par with a state-of-the-art marker-based method we compared our approach to. The presented study shows the feasibility of this novel approach, and yields promising results towards a purely IMU-based motion compensation in C-arm CT.
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