A novel augmented reality visualization in jaw surgery: enhanced ICP based modified rotation invariant and modified correntropy

Image registration, accuracy, processing time and occlusions are the main limitations of augmented reality (AR) based jaw surgery. Therefore, the main aim of this paper is to reduce the registration error, which will help in improving the accuracy and reducing the processing time. Also, it aims to remove outliers and remove the registration outcomes trapped in local minima to improve the alignment problems and remove the occlusion caused by surgery instrument. The enhanced Iterative Closest Point (ICP) algorithm with rotation invariant and correntropy was used for the proposed system. Markerless image registration technique was used for AR-based jaw surgery. The problem of occlusion caused by surgical tools and blood is solved by using stereo based tracing with occlusion handling techniques. This research reduced alignment error 0.59 mm?~?0.62 mm against 0.69?~?0.72 mm of state-of-the-art solution. The processing time of video frames was enhanced to 11.9?~?12.8 fps against 8?~?9.15 fps in state-of-the-art solution. This paper is focused on providing fast and accurate AR-based system for jaw surgery. The proposed system helps in improving the AR visualization during jaw surgery. The combination of methods and technology helped in improving AR visualization for jaw surgery and to overcome the failure caused by a large rotation angle and provides an initial parameter for better image registration. It also enhances performance by removing outliers and noises. The pose refinement stage provides a better result in terms of processing time and accuracy.