Hand-Eye Robot Aided Surgery For Total Knee Replacement And Pre-clinical Trials

With the rapid developments of medical theories, surgery operations have become more elaborate and complicated. State-of-art technologies, such as computer, robotics, electronic information and network communication, have been widely applied in medical areas. As a result, robot aided surgery (RAS) is increasingly adopted in modern clinic operations.Every year, thousands of patients suffered from joint diseases, such as rheumatoid arthritis or osteoarthritis, needing total knee replacement (TKR) surgery to recover their normal functions. Presently, the positioning of prosthetic components in surgeries mainly depends on clinic experiences of doctors and special surgical guiding devices. To avoid the limitations of jig-based TKR systems, robot/computer assisted surgeries are quickly developed, with the aid of which a better operation precision and surgical quality are well expected.However, the classical robot aided surgical systems of TKR has limitations in the operational precisions and twice surgeries. According to the characteristics of the TKR surgery, we designed a hand-eye robot aided surgical system and made it applicable to clinical trials. In this model, both the cameras and the cutting tool are fixed on the end-effecter of the robot. In this way, we get a dynamic navigation in stead of an inadequate static one. In total knee replacement surgeries, the information from fiducial marks helps the surgical robot to automatically determine the position of cutting planes. Using this method, an accurate mechanical axis is established.The major contributions of this thesis includes four pars: first, base on HERAS model, we designed and realize a pre-clinical experiment system, which can fulfill the requirement of clinical applications; second, we resolve the problem of online hand-eye calibration; third, we proposed new methods for motion segmentation; and at last, we applied HERAS model to TKR cadaver trials and resolve many problems in these experiments. Detailed descriptions of these contributions are as follows: 1) Design and realize a pre-clinical experiment system base on HERAS model. In this model, using the information of fiducial marks on the knee, one can establish a femur, tibia coordinate system and get an accurate mechanical axis. The system fulfills the requirements of cadaver trials and is very meaningful toward clinic applications.2) In order to guarantee the safety of surgeries, online hand-eye calibration will never be overlooked. After analyzing the traditional method of offline hand-eye calibration and online hand-eye calibration, we proposed a new concept of adaptive motion selection for online hand-eye calibration, which will not only avoid the degenerate cases, but also avoid small rotations that will lead large error in calibration.3) In the model of HERAS for TKR, we usually use several assistant guides simultaneously to track multiple motions. Based on the previous works of visual tracking and multibody motion segmentation, we proposed two new methods of segmenting multiple 3D motions from line correspondences--one is based on multibody trifocal tensor, while the other one is based on line optical flow.4) Moreover, we employed different materials, such as phantoms, animal bones, human bones and cadaver. We resolved practical problems in these experiments and made accuracy analysis. The experiences and technologies will be very helpful for the clinical surgery in the future.