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.
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.