RSIP Vision is attending AAOS 2026
New Orleans, LA – March 2 – 6, 2026 RSIP Vision is heading to AAOS in New Orleans from March 2–6, 2026 We’re bringing the
Tag: Orthopedic surgery
RSIP Vision will be at the Spine Summit in Phoenix, AZ
Phoenix, AZ – February 26, 2026 RSIP Vision will be at the Spine Summit in Phoenix, AZ, February 26–March 1, 2026 Meet our CEO Ron
RSIP Vision will be attending the SAGES NBT Innovation weekend
Houston , TX – February 19, 2026 We’re excited to announce that RSIP Vision will be attending the SAGES NBT Innovation weekend on February 19-21 in
Announcement – XPlan.ai Confirms Premier Precision in Peer-Reviewed Clinical Study of its 2D-to-3D Knee Reconstruction Solution
The study, featured in the prestigious Journal of Clinical Medicine, found sub-millimeter accuracy on real-world patient imaging, enabling widespread access to precise, image-based computer-assisted surgery
Announcement – XPlan.ai by RSIP Vision Presents Successful Preliminary Results from Clinical Study of it’s XPlan 2D-to-3D Knee Bones Reconstruction
A tool for reconstruction of a 3D model of the knee from 2D X-ray images is being evaluated on clinical data at a leading medical
Announcement – Total Shoulder Arthroplasty (TSA) Planning Through MRI Scan
RSIP Vision Presents New Tool for Total Shoulder Arthroplasty (TSA) Planning Through MRI Scan Advanced artificial intelligence creates accurate and radiation-free method for TSA planning.
Announcement – Registration Module for Orthopedic Surgery
RSIP Vision Announces Patient-Specific, Intraoperative Registration Module for Orthopedic Surgery The new neural network technology enables accurate, quantitative measurements of bones and implants during the
Announcement – Automated Assessment of Cartilage Damage
RSIP Vision Announces New Tool for Sports Medicine Applications, Enabling Automated Assessment of Cartilage Damage This new algorithmic software provides automated measurement of articular cartilage
AI for Navigation in Robotic Assisted Surgeries
Every Robotic Assisted Surgeries (RAS) requires some level of navigation. While in open surgery the target is viewed directly, minimally invasive RAS views come from
Announcement – RSIP Vision Launches a New Knee Segmentation and Landmark Detection from X-ray Module
Breakthrough AI technology leads to precise surgery and optimal implant positioning, resulting in improved quality of life for the patients. SILICON VALLEY, CA, September 15,
Announcement – RSIP Vision Announces Breakthrough AI technology for 3D Reconstruction of Knees from X-ray Images
RSIP Vision Announces Breakthrough AI technology for 3D Reconstruction of Knees from X-ray Images. New technology creates a rich 3D modelling of each knee bone
Segmentation in Orthopedics with Deep Learning
Segmentation is highly important both for examination and planning of knee replacement, hip replacement, shoulder surgery, lesion detection, osteotomy and many other orthopedic procedures. Deep Learning is repeatedly being proven to be the most powerful framework for various tasks, and segmentation in orthopedics is no exception. RSIP Vision’s CTO Ilya Kovler explains how to improve the segmentation in orthopedics thanks to AI and deep learning.
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Announcement – RSIP Vision Launches a Breakthrough AI-Based Shoulder Replacement Solution
RSIP Vision Launches a Breakthrough AI-Based Shoulder Replacement Solution, Dramatically Improving Clinical Outcome and Shortening Recovery Time. New Technology integrated in medical vendors’ platforms, allows
Announcement – RSIP Vision Launches AI-Based, 3D Total Hip Replacement Solution
SILICON VALLEY, Calif., Dec 17, 2019 — RSIP Vision, an Israeli global provider of artificial intelligence (AI), computer vision, and image processing technology, announced today a
Computer-Assisted Joint Replacement (hip and knee)
Pathologies in the joint regions are common especially among elderly patients. They are caused, in many cases, by wear and tear of the cartilage layer
Robots in Medical Applications
Machine Vision and AI for orthopedic surgery are extensively used in solutions enabling robotic surgical procedures and other medical applications. The robot’s hand being more precise than the surgeon, more and more surgeries are performed by properly equipped surgical robots. Besides the details of medical robotics applications, this article discusses also other medical systems, in particular Virtual Reality in medicine, by which RSIP Vision makes it possible to develop a simulator for complex and risky surgeries like brain surgeries.
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Validation of accuracy in navigation systems
System validation of accuracy is an offline procedure performed periodically to confirm that the tracking system is accurate. In some cases, validation of accuracy can
Navigation Systems in Orthopedic Surgery
The navigation system is one of the most powerful tools for the surgeon in orthopedic surgery. The visualization system aids the surgeon to place his
Registration of CT and X-ray
Registration is a phase of orthopedic surgeries in which a visualization system is called to support the surgeon. This system provides real time view of
CT Segmentation in orthopedic surgery
CT image segmentation is a typical phase of orthopedic surgeries in which a visualization system is called to visually support the surgeon’s task. This system
Calibration of X-ray images
This series of 5 articles by RSIP Vision about orthopedic navigation during surgery displays the state-of-the-art image processing techniques offering the surgeon a highly accurate and effective real time in-op view of the surgery environment. This procedure can be divided in several tasks: camera calibration of input images; segmentation during orthopedic surgeries; registration of CT and X-Ray; orientation and navigation during surgery; validation of accuracy in navigation systems. The outcome is a breakthrough advancement in orthopedic surgery performance, corroborated by rich academic literature supporting the method and by widespread use in the operation room.
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Density Measurement of Damaged Cartilage
Interpretation of ultrasound images of cartilage is challenging since they display no obvious borders in the transition between tissues: the boundary between tissues can morph in both density and texture. Our software can process these problematic ultrasound images and automatically measure the density of cartilage in the knee. The main benefits of this procedure are its non-invasive nature and the efficient and accurate measurement of the cartilage it provides.
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Anatomical surface reconstruction with sparse set of points
Advance navigation techniques in orthopedic surgery allow to construct 3D models of patients’ anatomical parts by matching a surface to an acquired set of data points. As an alternative to costly imaging procedures, ultrasound or fluoroscopic scan can be performed with much reduced costs and hazards. A set of surface points marked by the technician or physician forms then an initial sparse set for anatomical surface reconstruction. Here we show how RSIP Vision’s engineers overcome the challenge of using a sparse set of points to accurately reconstruct a complex 3d surface.
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3D Reconstruction for Bone Alignment
Advances in vision-based medical imaging have completely transformed orthopedic surgery planning and operation procedures. A practical example is a high-impact femur fracture, resulting in a noticeable separation into two segments of the femur. Surgery in such cases requires initial alignment of the proximal and distal parts of the broken bone, followed by insertion and securing of a nail. In RSIP Vision’s solution, image features are matched to a pre-designed flexible geometrical model of the bone.
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Point and surface registration in orthopedics
Point and surface registration enable computer vision and image processing to improve surgical orthopedy practices and affect surgery outcome recovery. Bringing point and surface registration in the field of orthopedics, computer vision and image processing hold the potential to improve surgical practices and affect surgery outcome to favor the benefit of patients and fast recovery. Measurement accuracy (within less than 1 mm) is a strict constraint to computer-vision-based algorithms.
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