Three Dimensional Microrobot Tracking Using Learning-based System - Pyo, Jang; Yoon, Siyeop; Vania, Malinda; Lee, Deukhee (INST CONTROL ROBOTICS & SYSTEMS, KOREAN INST ELECTRICAL ENGINEERS, 2020)
As a promising method for robotic catheter therapeutics, a controllable wireless microrobot system with a less invasive intraoperative procedure has been presented for thrombosis surgery. The controllable wireless microrobot utilizes an electromagnetic actuator system for microrobot actuation and biplane X-ray system for microrobot imaging. We propose the new 3D tracking method of microrobot for this system. As a learning-based system, cascade classifier was adapted for real-time microrobot tracking. Combination of cascade classifier and contour-based system made accurate microrobot detection method on 2D projected X-ray images. Kalman filter interpolated lost frames, and triangulation method reconstructed 3D pose (position and orientation) from 4 endpoints of microrobot pairs. Also, the semi-automatic calibration method for bi-plane C-arm devices was proposed by using modified shortest path algorithm. To find the optimal rescaling setting, 3D tracking accuracy was investigated according to the rescaling of original intensity values. The experiment results showed a good performance with tracking errors of 2.37 +/- 9.91mm in position and 6.53 +/- 13.80 degrees in orientation under 2200 optimal width of rescaling. If tracking evaluation is constrained under frames detected by cascade classifier, 3D tracking errors improved sincerely by 0.28 +/- 1.13mm in position and 3.48 +/- 2.89 degrees in orientation. The optimal width of the rescaling setting needed bigger value than the mean of intensity values. The proposed tracking technique accomplished a fast frame rate of 34.72 frames/sec under OpenCL implementation of OpenCV. Learning based system is robust to the change of graphics setting since training can adapt rapidly to this change. Also, proposed framework can cooperate with the change of microrobot shape if a contour-based method is optimized. 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.