Automatic feature-based markerless calibration and navigation method for augmented reality assisted dental treatment  

作　　者：Faizan Ahmad Jing Xiong Zeyang Xia 

机构地区：[1]Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences,Shenzhen,China [2]University of Chinese Academy of Sciences,Beijing,China [3]School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai,China

出　　处：《IET Cyber-Systems and Robotics》2024年第4期48-61,共14页智能系统与机器人(英文)

基　　金：Grant/Award Numbers:U2013205,62073309;Guangdong Basic and Applied Basic Research Foundation,Grant/Award Number:2022B1515020042;Shenzhen Science and Technology Program,Grant/Award Number:JCYJ20220818101603008。

摘　　要：Augmented reality(AR)is gaining traction in the field of computer-assisted treatment(CAT).Head-mounted display(HMD)-based AR in CAT provides dentists with enhanced visualisation by directly overlaying a three-dimensional(3D)model on a real patient during dental treatment.However,conventional AR-based treatments rely on optical markers and trackers,which makes them tedious,expensive,and uncomfortable for dentists.Therefore,a markerless image-to-patient tracking system is necessary to overcome these challenges and enhance system efficiency.This paper proposes a novel feature-based markerless calibration and navigation method for an HMD-based AR visualisation system.The authors address three sub-challenges:firstly,synthetic RGB-D data for anatomical landmark detection is generated to train a deep convolutional neural network(DCNN);secondly,the HMD is automatically calibrated using detected anatomical landmarks,eliminating the need for user input or optical trackers;and thirdly,a multi-iterative closest point(ICP)algorithm is developed for effective 3D-3D real-time navigation.The authors conduct several experiments on a commercially available HMD(HoloLens 2).Finally,the authors compare and evaluate the approach against state-ofthe-art methods that employ HoloLens.The proposed method achieves a calibration virtual-to-real re-projection distance of(1.09�0.23)mm and navigation projection errors and accuracies of approximately(0.53�0.19)mm and 93.87%,respectively.

关 键 词：motion estimation NAVIGATION sensor calibration 

分 类 号：R72[医药卫生—儿科]