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The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS|November 21, 2022
Autonomous path planning for robot-assisted pelvic fracture closed reduction with collision avoidanceMingzhang Pan, Yuan Chen, Zhen Li, et al.
The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS|January 11, 2021
A novel solution of using mixed reality in bowel and oral and maxillofacial surgical telepresence: 3D mean value cloning algorithmArjina Maharjan, Abeer Alsadoon, P W C Prasad, et al.
The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS|June 1, 2021
Evaluation of how users interface with holographic augmented reality surgical scenes: Interactive planning MR-Guided prostate biopsiesJose D Velazco-Garcia, Nikhil V Navkar, Shidin Balakrishnan, et al.
The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS|October 30, 2020
Robotic limited local resection of duodenal juxta-ampullary neoplasmsHye Jung Cho, Jae Young Jang, Sung Yub Jeong, et al.
The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS|September 21, 2016
Data-driven methods towards learning the highly nonlinear inverse kinematics of tendon-driven surgical manipulatorsWenjun Xu, Jie Chen, Henry Y K Lau, et al.
The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS|May 26, 2017
Robotic distal locking of intramedullary nailing: Technical description and cadaveric testingMartin Panzica, Eduardo M Suero, Ralf Westphal, et al.
The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS|February 3, 2022
Analysis of executional and procedural errors in dry-lab robotic surgery experimentsKay Hutchinson, Zongyu Li, Leigh A Cantrell, et al.
The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS|January 31, 2022
Markerless registration approach using dynamic touchable region modelHang Phuong Nguyen, Taeho Kim, Sungmin Kim
The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS|February 8, 2022
Machine-learning-based approach for predicting postoperative skeletal changes for orthognathic surgical planningQingchuan Ma, Etsuko Kobayashi, Bowen Fan, et al.
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