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A novel rotational matrix and translation vector algorithm: geometric accuracy for augmented reality in oral and maxillofacial surgeries
Author(s) -
Murugesan Yahini Prabha,
Alsadoon Abeer,
Manoranjan Paul,
Prasad P.W.C.
Publication year - 2018
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.1889
Subject(s) - computer science , translation (biology) , augmented reality , computer vision , overlay , artificial intelligence , depth perception , frame rate , algorithm , polygon mesh , perception , computer graphics (images) , biochemistry , chemistry , neuroscience , biology , messenger rna , gene , programming language
Background Augmented reality‐based surgeries have not been successfully implemented in oral and maxillofacial areas due to limitations in geometric accuracy and image registration. This paper aims to improve the accuracy and depth perception of the augmented video. Methodology The proposed system consists of a rotational matrix and translation vector algorithm to reduce the geometric error and improve the depth perception by including 2 stereo cameras and a translucent mirror in the operating room. Results The results on the mandible/maxilla area show that the new algorithm improves the video accuracy by 0.30–0.40 mm (in terms of overlay error) and the processing rate to 10–13 frames/s compared to 7–10 frames/s in existing systems. The depth perception increased by 90–100 mm. Conclusion The proposed system concentrates on reducing the geometric error. Thus, this study provides an acceptable range of accuracy with a shorter operating time, which provides surgeons with a smooth surgical flow.