  Background and aim: Image registration and alignment are the main limitations
of augmented reality-based 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 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, for example, forwards and
backwards directional cloud point, the iteration on image registration was
decreased. This has led to improve the 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 movement of 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 knee such as femur, tibia, cartilage, blood vessels,
etc.
