School of Mechanical Engineering, Chonnam National University, Gwangju, 61186, South Korea.
Medical Microrobot Center, Robot Research Initiative, Chonnam National University, Gwangju, 61186, South Korea.
Int J Comput Assist Radiol Surg. 2018 Nov;13(11):1843-1852. doi: 10.1007/s11548-018-1846-z. Epub 2018 Aug 20.
As a promising intravascular therapeutic approach for autonomous catheterization, especially for thrombosis treatment, a microrobot or robotic catheter driven by an external electromagnetic actuation system has been recently investigated. However, the three-dimensional (3D) real-time position and orientation tracking of the microrobot remains a challenge for precise feedback control in clinical applications owing to the micro-size of the microrobot geometry in vessels, along with bifurcation and vulnerability. Therefore, in this paper, we propose a 3D posture recognition method for the unmanned microrobotic surgery driven by an external electromagnetic actuator system.
We propose a real-time position and spatial orientation tracking method for a millimeter-sized intravascular object or microrobot using a principal component analysis algorithm and an X-ray reconstruction. The suggested algorithm was implemented to an actual controllable wireless microrobot system composed of a bullet-shaped object, a biplane X-ray imaging device, and an electromagnetic actuation system. Numerical computations and experiments were conducted for the performance verification.
The experimental results showed a good performance of the implemented system with tracking errors less than 0.4 mm in position and 2° in orientation. The proposed tracking technique accomplished a fast processing time, ~ 0.125 ms/frame, and high-precision recognition of the micro-sized object.
Since the suggested method does not require pre-information of the object geometry in the human body for its 3D shape and position recognition, it could be applied to various elliptical shapes of the microrobot system with computation time efficacy and recognition accuracy. Hence, the method can be used for therapeutic millimeter- or micron-sized manipulator recognition in vascular, as well as implanted objects in the human body.
作为一种有前途的自主导管介入治疗方法，特别是用于血栓治疗，最近研究了一种由外部电磁激励系统驱动的微机器人或机器人导管。然而，由于微机器人在血管中的几何形状微小，以及分叉和脆弱性，微机器人的三维（3D）实时位置和姿态跟踪仍然是临床应用中精确反馈控制的挑战。因此，在本文中，我们提出了一种用于外部电磁激励系统驱动的无人微机器人手术的 3D 姿态识别方法。
我们提出了一种使用主成分分析算法和 X 射线重建的毫米级血管内物体或微机器人的实时位置和空间姿态跟踪方法。所提出的算法已应用于由子弹形物体、双平面 X 射线成像设备和电磁激励系统组成的实际可控无线微机器人系统。进行了数值计算和实验以验证性能。
实验结果表明，所实现的系统具有良好的性能，位置跟踪误差小于 0.4mm，方向跟踪误差小于 2°。所提出的跟踪技术实现了快速的处理时间，约为 0.125ms/帧，并且能够高精度识别微尺寸物体。
由于所提出的方法不需要人体内部物体的三维形状和位置的先验信息，因此它可以应用于各种具有计算时间效率和识别精度的微机器人系统的椭圆形形状。因此，该方法可用于血管内治疗毫米或微米级操纵器的识别，以及人体植入物的识别。
