Tag: Knee

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 – 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 – 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.

Announcement – Knee Replacement by RSIP Vision

Knee Replacement Patients Enjoy Life-Changing Surgical Outcomes with RSIP Vision’s Revolutionary AI Solution Jerusalem, May 29, 2019 – RSIP Vision, a global leader in artificial

Ultrasound Imaging of Speckled Cartilage Tissue

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.

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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Tag: Knee

Announcement – XPlan.ai by RSIP Vision Presents Successful Preliminary Results from Clinical Study of it’s XPlan 2D-to-3D Knee Bones Reconstruction

Announcement – Registration Module for Orthopedic Surgery

Announcement – RSIP Vision Launches a New Knee Segmentation and Landmark Detection from X-ray Module

Announcement – RSIP Vision Announces Breakthrough AI technology for 3D Reconstruction of Knees from X-ray Images

Segmentation in Orthopedics with Deep Learning

Announcement – Knee Replacement by RSIP Vision

Density Measurement of Damaged Cartilage

Point and surface registration in orthopedics

Get in touch

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Announcement – XPlan.ai by RSIP Vision Presents Successful Preliminary Results from Clinical Study of it’s XPlan 2D-to-3D Knee Bones Reconstruction

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