School of Mechanical Engineering, Tianjin University, Tianjin, 300072, China.
School of Life Science and Technology, Harbin Institute of Technology, Harbin, 150001, China.
Int J Comput Assist Radiol Surg. 2018 Apr;13(4):573-583. doi: 10.1007/s11548-018-1708-8. Epub 2018 Feb 7.
In many clinical procedures such as cryoablation that involves needle insertion, accurate placement of the needle's tip at the desired target is the major issue for optimizing the treatment and minimizing damage to the neighboring anatomy. However, due to the interaction force between the needle and tissue, considerable error in intraoperative tracking of the needle tip can be observed as needle deflects.
In this paper, measurements data from an optical sensor at the needle base and a magnetic resonance (MR) gradient field-driven electromagnetic (EM) sensor placed 10 cm from the needle tip are used within a model-integrated Kalman filter-based sensor fusion scheme. Bending model-based estimations and EM-based direct estimation are used as the measurement vectors in the Kalman filter, thus establishing an online estimation approach.
Static tip bending experiments show that the fusion method can reduce the mean error of the tip position estimation from 29.23 mm of the optical sensor-based approach to 3.15 mm of the fusion-based approach and from 39.96 to 6.90 mm, at the MRI isocenter and the MRI entrance, respectively.
This work established a novel sensor fusion scheme that incorporates model information, which enables real-time tracking of needle deflection with MRI compatibility, in a free-hand operating setup.
在许多临床操作中，如涉及到针插入的冷冻消融术，将针尖准确地放置在所需的目标位置是优化治疗和最小化邻近解剖结构损伤的主要问题。然而，由于针和组织之间的相互作用力，在术中跟踪针尖时，由于针的偏转，会观察到相当大的误差。
在本文中，使用位于针基底部的光学传感器和距离针尖 10 厘米处的磁共振（MR）梯度场驱动的电磁（EM）传感器的测量数据，在基于模型集成卡尔曼滤波器的传感器融合方案中。基于弯曲模型的估计和基于 EM 的直接估计被用作卡尔曼滤波器中的测量向量，从而建立了一种在线估计方法。
静态尖端弯曲实验表明，融合方法可以将基于光学传感器的方法的尖端位置估计的平均误差从 29.23 毫米降低到融合方法的 3.15 毫米，分别在 MRI 等中心点和 MRI 入口处。
这项工作建立了一种新的传感器融合方案，该方案结合了模型信息，在自由操作设置下实现了与 MRI 兼容的实时跟踪针的偏转。
