Deep segmentation leverages geometric pose estimation in computer‐aided total knee arthroplasty

Author:

Rodrigues Pedro1ORCID,Antunes Michel2,Raposo Carolina2,Marques Pedro3,Fonseca Fernando3,Barreto Joao P.12

Affiliation:

1. Institute of Systems and Robotics University of Coimbra Coimbra Portugal

2. Perceive 3D Coimbra Portugal

3. Faculty of Medicine Coimbra Hospital and University Centre Coimbra Portugal

Publisher

Institution of Engineering and Technology (IET)

Subject

Health Information Management,Health Informatics

Reference16 articles.

1. Projections of Primary and Revision Hip and Knee Arthroplasty in the United States from 2005 to 2030

2. Smith & Nephew: ‘Navio surgical system’. Available athttp://smithnephewlivesurgery.com/navio‐surgical‐system accessed 29 March 2019

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1. Joint Track Machine Learning: An Autonomous Method of Measuring Total Knee Arthroplasty Kinematics From Single-Plane X-Ray Images;The Journal of Arthroplasty;2023-10

2. Ensemble of 6 DoF Pose estimation from state-of-the-art deep methods.;Neurocomputing;2023-07

3. BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objects;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW);2023-06

4. Pose Quality Prediction for Vision Guided Robotic Shoulder Arthroplasty;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29

5. Evaluation of single-stage vision models for pose estimation of surgical instruments;International Journal of Computer Assisted Radiology and Surgery;2023-04-30

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