A Novel Visualization System of Using Augmented Reality in Knee Replacement Surgery: Enhanced Bidirectional Maximum CorrentropyAlgorithm

Abstract

Background and aim: Image registration and alignment are the main limitations of augmented realitybased knee replacement surgery. This research aims to decrease the registration error, eliminate outcomes that are trapped in local minima to improve the alignment problems, handle the occlusion and maximize the overlapping parts. Methodology: markerless image registration method was used for Augmented reality-based knee replacement surgery to guide and visualize the surgical operation. While weight least square algorithm was used to enhance stereo camera-based tracking by filling border occlusion in right to left direction and non-border occlusion from the left to right direction. Results: This study has improved video precision to 0.57 mm ~ 0.61 mm alignment error. Furthermore, with the use of bidirectional points, i.e. Forwards and backward directional cloud points, the iteration on image registration was decreased. This has led to the improved processing time as well. The processing time of video frames was improved to 7.4 ~11.74 fps. Conclusions: It seems clear that this proposed system has focused on overcoming the misalignment difficulty caused by the movement of the patient and enhancing the AR visualization during knee replacement surgery. The proposed system was reliable and favorable which helps in eliminating alignment error by ascertaining the optimal rigid transformation between two cloud points and removing the outliers and non-Gaussian noise. The proposed augmented reality system helps in accurate visualization and navigation of anatomy of the knee such as femur, tibia, cartilage, blood vessels, etc.