RSIP Vision announced a novel 2D to 3D registration module that will improve the execution of orthopedic surgeries, such as total hip arthroplasty. Utilizing a proprietary neural network, trained on patient-specific imaging, this module will enable powerful, automated intra-operative assessments in real time of the true location and positioning of the implants and bones increasing accuracy and improving the surgery execution. This is achieved by matching a pre-operative CT to intraoperative fluoroscopy and giving the surgeon a real time indication accordingly. The solution aims to increase the efficiency of both the planning and execution phases of hip replacement surgery through automated landmark detection and measurement of anatomical relationships.
The new module joins a vast suite of orthopedic image analysis tools for pre-operative planning and intraoperative navigation developed by RSIP Vision. It leverages a unique, AI-based, patient-specific image registration algorithm developed in RSIP’s innovation lab and is being offered to the leading implant and medical imaging companies to power specific, intraoperative procedures, such as hip replacement surgical solutions. In parallel to the initial capability of 2D-to-3D femur and pelvis registration, RSIP is developing additional modules for implant hardware registration as well as a 3D anatomical measurements suite, to be offered in the near future.
As the surgeon moves throughout the various stages of the procedure, the system recognizes and updates changes from the pre-operative condition to confirm that the components are in their desirable positions. This novel AI-based approach will be unique in its ability to robustly register and detect anatomical landmarks in real time, opening a host of advanced applications.
RSIP Vision announced a novel 2D to 3D registration module that will improve the execution of orthopedic surgeries, such as total hip arthroplasty. Utilizing a proprietary neural network, trained on patient-specific imaging, this module will enable powerful, automated intra-operative assessments in real time of the true location and positioning...
RSIP Vision announced a novel 2D to 3D registration module that will improve the execution of orthopedic surgeries, such as total hip arthroplasty. Utilizing a proprietary neural network, trained on patient-specific imaging, this module will enable powerful, automated intra-operative assessments in real time of the true location and positioning of the implants and bones increasing accuracy and improving the surgery execution. This is achieved by matching a pre-operative CT to intraoperative fluoroscopy and giving the surgeon a real time indication accordingly. The solution aims to increase the efficiency of both the planning and execution phases of hip replacement surgery through automated landmark detection and measurement of anatomical relationships.
The new module joins a vast suite of orthopedic image analysis tools for pre-operative planning and intraoperative navigation developed by RSIP Vision. It leverages a unique, AI-based, patient-specific image registration algorithm developed in RSIP’s innovation lab and is being offered to the leading implant and medical imaging companies to power specific, intraoperative procedures, such as hip replacement surgical solutions. In parallel to the initial capability of 2D-to-3D femur and pelvis registration, RSIP is developing additional modules for implant hardware registration as well as a 3D anatomical measurements suite, to be offered in the near future.
As the surgeon moves throughout the various stages of the procedure, the system recognizes and updates changes from the pre-operative condition to confirm that the components are in their desirable positions. This novel AI-based approach will be unique in its ability to robustly register and detect anatomical landmarks in real time, opening a host of advanced applications.
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