RSIP Vision introduced an advanced joint segmentation tool for detailed, non-invasive planning of revision arthroplasty and other orthopedic procedures for patients with pre-existing metal implants. This artificial intelligence-based software module enables rapid segmentation of different joints from CT scans of hip, knee, shoulder and spine. It provides precise measurements of the geometry of joints, including complicated cases of joints with existing metallic orthopedic implants.
RSIP Vision’s deep learning algorithms provide a solution for the artifacts associated with metals in CT images, which normally cause degradation of medical imaging. This vendor-neutral technology will be available to third-party CT manufacturers and medical device vendors, allowing them an improved way to plan and execute both manual and robot-assisted revision arthroplasty procedures.
This module features accurate discernment of the location of metals in the bones, resulting in uniform, accurate and robust segmentation of all the different elements of both bones and implants, as well as exact delineation of metal fragments from the bones. This leads to better preparation and setting of expectations with the patient. In addition, preparing the required implants rather than all the various options makes it more financially beneficial.
This technology may be used in a wide variety of orthopedic use cases, including periprosthetic fractures around implants or fusions, local recurrence of tumors in the presence of implants and repeat femoral neck fracture after fusion.
This latest module joins RSIP’s offerings for knee, shoulder and hip reconstruction planning.
RSIP Vision introduced an advanced joint segmentation tool for detailed, non-invasive planning of revision arthroplasty and other orthopedic procedures for patients with pre-existing metal implants. This artificial intelligence-based software module enables rapid segmentation of different joints from CT scans of hip, knee, shoulder and spine....
RSIP Vision introduced an advanced joint segmentation tool for detailed, non-invasive planning of revision arthroplasty and other orthopedic procedures for patients with pre-existing metal implants. This artificial intelligence-based software module enables rapid segmentation of different joints from CT scans of hip, knee, shoulder and spine. It provides precise measurements of the geometry of joints, including complicated cases of joints with existing metallic orthopedic implants.
RSIP Vision’s deep learning algorithms provide a solution for the artifacts associated with metals in CT images, which normally cause degradation of medical imaging. This vendor-neutral technology will be available to third-party CT manufacturers and medical device vendors, allowing them an improved way to plan and execute both manual and robot-assisted revision arthroplasty procedures.
This module features accurate discernment of the location of metals in the bones, resulting in uniform, accurate and robust segmentation of all the different elements of both bones and implants, as well as exact delineation of metal fragments from the bones. This leads to better preparation and setting of expectations with the patient. In addition, preparing the required implants rather than all the various options makes it more financially beneficial.
This technology may be used in a wide variety of orthopedic use cases, including periprosthetic fractures around implants or fusions, local recurrence of tumors in the presence of implants and repeat femoral neck fracture after fusion.
This latest module joins RSIP’s offerings for knee, shoulder and hip reconstruction planning.
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