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A novel visualization system of using augmented reality in knee replacement surgery: Enhanced bidirectional maximum correntropy algorithm
Author(s) -
Maharjan Nitish,
Alsadoon Abeer,
Prasad P.W.C.,
Abdullah Salma,
Rashid Tarik A.
Publication year - 2021
Publication title -
the international journal of medical robotics and computer assisted surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 53
eISSN - 1478-596X
pISSN - 1478-5951
DOI - 10.1002/rcs.2223
Subject(s) - computer science , augmented reality , computer vision , artificial intelligence , visualization , point cloud , knee replacement , outlier , algorithm , medicine , surgery , arthroplasty
Background and Aim Image registration and alignment are the main limitations of augmented reality (AR)‐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 AR‐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 0.57–0.61 mm alignment error. Furthermore, with the use of bidirectional points, that is, forward and backward 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 frames per second. Conclusions It seems clear that this proposed system has focused on overcoming the misalignment difficulty caused by the movement of patient and enhancing the AR visualization during knee replacement surgery. The proposed system was reliable and favourable 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 AR system helps in accurate visualization and navigation of anatomy of knee such as femur, tibia, cartilage, blood vessels and so forth.