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: Reconstruction
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 – New Urological AI Tool for 3D Reconstruction of the Ureter
RSIP Vision Presents New Urological AI Tool for 3D Reconstruction of the Ureter Improving Urological Procedures Innovative technology utilizes 2D fluoroscopic images and reconstructs an
Announcement – Non-Invasive Planning of Coronary Intervention
RSIP Vision Presents New Technology for Non-Invasive Planning of Coronary Intervention Innovative technology provides accurate coronary artery 3D reconstruction from 2D angiography to be used
Announcement – Bladder Panorama Generator and Sparse Reconstruction Tool
RSIP Vision Introduces Bladder Panorama Generator and Sparse Reconstruction Tool New modules perform stitching of bladder images during cystoscopies, creating a panoramic view and provides
Enhanced ERCP tumor assessment using AI
ERCP involves both endoscopy and fluoroscopy on a region with limited access. Accordingly, it poses several challenges for the gastroenterologist performing the procedure: imaging and artificial intelligence are key technologies to solve these challenges. They are used to reconstruct multiangle 2D X-ray images into a 3D image that will help the gastroenterologists in real-time navigation, reducing any complications involved in the navigation process. AI can be trained to accurately classify each tumor found by ERCP and check whether it is cancerous or not.
Read More
AI and Robotic Surgery for Renal Cancer
Image analysis techniques and artificial intelligence are leading to radical innovations in renal cancer diagnosis and treatment. In particular, renal cancer robotic surgery. Advanced AI algorithms and computer vision assist in detecting and classifying all kinds of renal diseases, using segmentation and contour detection. This results in improved diagnostic accuracy and enhanced personalized treatment for patients. Moreover, robotic assistance in renal surgeries has gained increased traction in both complete and partial nephrectomies. Surgical planning and 3D reconstruction based on CT and MRI images play vital roles in successful robotic-assisted kidney-related procedures
High Resolution Image Reconstruction
Recovering a high-resolution (HR) image from a low resolution one is a classical problem in computer vision for which many algorithms have been developed to
3D surface reconstruction from single depth view
The advances in the manufacturing of depth sensors and camera technologies, such as LIDAR and RealSense cameras, have brought three-dimensional (3D) applications to the front
Three-dimensional reconstruction
Three-dimensional reconstruction of scene can be viewed as is the reproduction of a depth-map. Thus, as an input we have a sequence of images as
Three-dimensional reconstruction of a deformable object
Reconstruction of the three-dimensional surface of an object based on single view 2-D sequence of images is a highly challenging task. Challenges stem in part
3D reconstruction of the heart
Using minimal 2D images from a routine angiography, RSIP Vision’s algorithm tracks the veins and constructs a route map of the arteries, from two different angles. Our sophisticated algorithms applied to computer vision in cardiology reconstruct 3D models of the heart artery tree from 2D images, allowing for improved diagnostic capabilities, lower risk to both patients and physicians, more effective therapy and reduced costs.
Read More
3D object reconstruction by fringe projection
Fringe pattern projection for 3D object reconstruction has been around for 3 decades. The method finds its application in reconstructing static and dynamic objects in
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.
Read More
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.
Read More
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.
Read More
Get in touch
Please fill the following form and our experts will be happy to reply to you soon
Recent News
Upcoming Events
SAGES | Tampa, FL
March 25 - 28 2026
AUA | Washington, DC
May 15 - 18 2026
ATS | Orlando, FL
May 17 - 20 2026
Find quick answers here
© All rights reserved to RSIP Vision 2023