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Towards markerless computer assisted surgery: Application to total knee arthroplasty
Author(s) -
Sta Salaheddine,
Ogor Jérôme,
Letissier Hoel,
Stindel Eric,
Hamitouche Chafiaa,
Dardenne Guillaume
Publication year - 2021
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.2296
Subject(s) - computer science , total knee arthroplasty , orthopedic surgery , computer assisted surgery , computer vision , artificial intelligence , point (geometry) , knee flexion , pose , arthroplasty , orthodontics , medicine , surgery , mathematics , geometry
Purpose A new approach is proposed to localise surgical instruments for Computer Assisted Orthopaedic Surgery (CAOS) that aims at overpassing the limitations of conventional CAOS solutions. This approach relies on both a depth sensor and a 6D pose estimation algorithm. Methods The Point‐Pair Features (PPF) algorithm was used to estimate the pose of a Patient‐Specific Instrument (PSI) for Total Knee Arthroplasty (TKA). Four depth sensors have been compared. Three scores have been computed to assess the performances: The Depth Fitting Error (DFE), the Pose Errors, and the Success Rate. Results The obtained results demonstrate higher performances for the Microsoft Kinect Azure in terms of DFE. The Occipital Structure core shows better behavior in terms of Pose Errors and Success Rate. Conclusion This comparative study presents the first depth‐sensor based solution allowing the intraoperative markerless localization of surgical instruments in orthopedics.