Research on Accuracy of Augmented Reality Surgical Navigation System Based on Multi-View Virtual and Real Registration Technology

Zhang, Fengfeng; Chen, Long; Miao, Wenhua; Sun, Lining

doi:10.1109/access.2020.3007178

Cited by 7 publications

(2 citation statements)

References 46 publications

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“…Augmented reality (AR) technologies have been applied to various fields, such as driving [1], [2], human-robot collaboration [7], surgical navigation [8], education [9], and manufacturing task assistance [10]. This section focuses on and reviews previous studies related to providing driving assistance information using AR-based visualizations.…”

Section: Related Workmentioning

confidence: 99%

Augmented Reality-Based Navigation Using Deep Learning-Based Pedestrian and Personal Mobility User Recognition—A Comparative Evaluation for Driving Assistance

Roh

Lee

2023

IEEE Access

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Recently, research on augmented reality-based head-up displays (AR-HUDs) for driving assistance has been widely conducted in the automotive industry. The disadvantage of having to look away from the road while driving can be compensated by using AR-HUD-based visualization instead of an auxiliary display on the central dashboard. As the number of personal mobility users on the road increases, and their moving speed is considerably faster than pedestrians, personal mobility makes it more difficult for the driver to cope with dangerous situations. However, there is little research work for considering personal mobility users for driving assistance. This study aims to enhance the driver's situational awareness to respond to unexpected situation by providing driver assistance information on the AR-HUD by combining deep learning and AR. In particular, the deep learning-based anomaly detection method can recognize personal mobility users effectively. This study also investigates the driver's understanding of the relationship between the amount of prioritized information provided to AR-HUD and situational cognitive ability. This understanding can be used to adjust the amount of information displayed on the AR-HUD to maintain drivers' situational awareness. The proposed approach was evaluated through an online study. The results showed that the proposed deep learning-based AR-HUD system improved the driver's situational awareness and showed advantages in driving assistance compared to the typical system.

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Section: Related Workmentioning

confidence: 99%

Augmented Reality-Based Navigation Using Deep Learning-Based Pedestrian and Personal Mobility User Recognition—A Comparative Evaluation for Driving Assistance

Roh

Lee

2023

IEEE Access

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“…For direct tracking and indirect tracking methods in terms of marker movement measurement, in vitro markers are mainly sensed by optical localization or mechanical motion localization methods, which have high accuracy and reliability under the right detection conditions. However, when the marker target is in vivo, optical localization methods cannot operate due to the occlusion problems [22,23]. In this case, it is necessary to use imaging methods such as ultrasound, CT, or electromagnetic positioning to achieve the movement measurement of the markers in vivo.…”

Section: Introductionmentioning

confidence: 99%

Research on Intraoperative Organ Motion Tracking Method Based on Fusion of Inertial and Electromagnetic Navigation

et al. 2021

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The intraoperative movement of target organs is currently a key and difficult problem that restricts clinical surgery diagnosis and treatment, especially radiotherapy. Unexpected posture changes can cause the deviation of the target area during the operation, thereby affecting the treatment effect and even causing severe complications. Therefore, it is necessary to track the movement of target organs in real-time and accurately to improve the effect and safety of the surgical treatment. This paper proposes an intraoperative organ motion tracking method based on the fusion of inertial navigation and electromagnetic navigation., which can directly measure the target organ's movement under non-invasive or minimally invasive conditions using the human natural cavity. The proposed method for identifying the magnetic field's interference state uses the extended Kalman filter to fuse the inertial measurement unit and the electromagnetic positioning information to achieve target organ movement tracking under different interference conditions. It effectively improved the real-time and robustness of intraoperative organ tracking. Simultaneously, based on the 9-axis inertial measurement unit and a 6-DOF electromagnetic positioning system, the catheter-type target organ tracker was developed, and then under the simulated electromagnetic interference environment, dynamic and static verification experiments were carried out, respectively. The maximum tracking error of displacement and attitude is 2.75 mm and 0.127 rad, respectively, under severe electromagnetic disturbance through experiments. Under non-electromagnetic interference conditions, its displacement and attitude's maximum tracking errors are 0.94 mm and 0.011 rad, respectively. The results prove that the target organ tracking method based on the fusion of inertial navigation and electromagnetic navigation is feasible. It can realize the tracking and measurement of the target organ's movement within the clinical permission error range.INDEX TERMS Inertial navigation, target organ tracking, intraoperative navigation; fusion algorithm.

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A fully automatic surgical registration method for percutaneous abdominal puncture surgical navigation

Li¹,

Deng²,

Shen³

et al. 2021

Computers in Biology and Medicine

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Research on Accuracy of Augmented Reality Surgical Navigation System Based on Multi-View Virtual and Real Registration Technology

Cited by 7 publications

References 46 publications

Augmented Reality-Based Navigation Using Deep Learning-Based Pedestrian and Personal Mobility User Recognition—A Comparative Evaluation for Driving Assistance

Augmented Reality-Based Navigation Using Deep Learning-Based Pedestrian and Personal Mobility User Recognition—A Comparative Evaluation for Driving Assistance

Research on Intraoperative Organ Motion Tracking Method Based on Fusion of Inertial and Electromagnetic Navigation

A fully automatic surgical registration method for percutaneous abdominal puncture surgical navigation

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