Influence of multiangle input of intraoperative fluoroscopic images on the spatial positioning accuracy of the Carm calibrationbased algorithm of a CAOS system Intraoperative fluoroscopic images, as one of the most important input data for computerassisted orthopedic surgery (CAOS) systems, have a significant influence on the positioning accuracy of CAOS system. In this study, we proposed to use multiangle intraoperative fluoroscopy images as input based on real clinical scenario, and the aim was to analyze the positioning accuracy and the error propagation rules with multiangle input images compared with traditional two input images. In the experiment, the positioning accuracy of the Carm calibrationbased algorithm was studied, respectively, using two, three, four, five, and six intraoperative fluoroscopic images as input data. Moreover, the error propagation rules of the positioning error were analyzed by the Monte Carlo method. The experiment result showed that increasing the number of multiangle input fluoroscopic images could reduce the positioning error of CAOS system, which has dropped from 1.01 to 0.61 mm. The Monte Carlo simulation analysis showed that for random input errors subject to normal distribution (xcexbc  0, xcfx83  1), the image positioning error dropped from 0.29 to 0.23 mm, and the staff gauge positioning error dropped from 1.36 to 1.19 mm, while the tracking device positioning error dropped from 3.41 to 2.13 mm. In addition, the results showed that image positioning error and staff gauge positioning error were all nonlinear error for the whole system, but tracker device positioning error was a strictly linear error. In conclusion, using multiangle fluoroscopy images was helpful for clinic, which could improve the positioning accuracy of the CAOS system by nearly 30%.

Development of a Novel Handeye Coordination Algorithm for Robot Assisted Minimally Invasive Surgery * The minimally invasive surgical robot greatly improved surgical OR efficiency, and surgeon manipulates the surgical instruments through masterslave control under the guidance of laparoscope vision. As a mapping of the surgeonu0027s handeye coordination, the coordination between surgical instruments and laparoscope has an important impact on the surgical efficiency and the ergonomics. In this paper, a novel handeye coordination algorithm is proposed for the robot assisted minimally invasive surgery (RMIS). Firstly, a novel cascadecalibration (CC) algorithm structure is proposed to determine the pose relationship between the robot laparoscope arm coordinate system and the robot instruments arm coordinate system. A handeye coordination algorithm is also proposed, which provides accurate masterslave control and improves the surgical operation room (OR) efficiency. We validate the proposed algorithm through two experiments with our minimally invasive surgical robot system. Our experiments demonstrate that the proposed method is competitively effective to induce the handeye coordination for the RMIS.