We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
ARAB HEALTH - INFORMA

Download Mobile App




Events

27 Jan 2025 - 30 Jan 2025
15 Feb 2025 - 17 Feb 2025

AI Tool Enables Total Shoulder Arthroplasty (TSA) Planning Through MRI Scan

By HospiMedica International staff writers
Posted on 04 Mar 2022
Print article
Image: Total Shoulder Arthroplasty (TSA) planning tool (Photo courtesy of RSIP Vision Ltd.)
Image: Total Shoulder Arthroplasty (TSA) planning tool (Photo courtesy of RSIP Vision Ltd.)

A new tool for Total Shoulder Arthroplasty (TSA) planning performs segmentation of the shoulder bones from shoulder MRI scan, which is usually performed in shoulder healthcare. The segmentation output undergoes super-resolution enhancement to overcome inherent MRI resolution limitations. The end-result is a high-quality, 3D model of the shoulder bones, which allows exceptional planning for TSA, without the need for a CT scan for planning.

This new vendor-neutral technology solution from RSIP Vision Ltd. (Jerusalem, Israel) is available to third-party MRI manufacturers and viewer solutions, allowing an accurate and radiation-free method for TSA planning. Shoulder injuries often require a diagnostic MRI scan, mainly to rule out soft-tissue damage. When approaching TSA, current practice requires a CT scan for procedural planning as CT resolution is superior to that of MRI. However, an additional CT scan involves exposing the patient to harmful radiation, as well as additional healthcare expenses.

RSIP Vision’s new tool utilizes the shoulder MRI scan, without compromising on resolution quality. It automatically segments the humerus and scapula from the scan. The segmentation output goes through another neural network, trained to upgrade segmentation resolution, thus producing a super-resolution model despite the original scan limitations. This output is as-good as CT-based models, without the need for an additional scan, and can be used for procedural planning.

“Shoulder MRI scans are common in shoulder pain management healthcare, usually for soft tissue analysis,” said Ron Soferman, CEO at RSIP Vision. “Deep learning (DL) algorithms can be developed for accurate segmentation of the shoulder bones. Neural networks are trained to process the resulting segmentation into a CT-grade segmentation, improving the original MRI resolution. Further down the line this tool can be altered to segment soft tissue, as well as other anatomies. This tool improves shoulder healthcare as it removes the need for a CT scan and its accompanying radiation and cost.”

“As a physician, you want to reduce radiation exposure to your patient,” said Dr. Shai Factor, orthopedic surgeon at Tel-Aviv Medical Center. “This new tool by RSIP Vision will utilize existing shoulder MRI scans, which we use routinely to demonstrate associated soft tissue pathologies, and will offer a radiation-free alternative to patients prior to shoulder arthroplasty, without compromising the 3D model’s quality.”

Related Links:
RSIP Vision Ltd. 

New
Gold Member
X-Ray QA Meter
T3 AD Pro
Gold Member
Real-Time Diagnostics Onscreen Viewer
GEMweb Live
New
Vertebral Body Replacement System
Hydrolift
New
Pneumatic Stool
Avante 5-Leg Pneumatic Stool

Print article

Channels

Patient Care

view channel
Image: The portable biosensor platform uses printed electrochemical sensors for the rapid, selective detection of Staphylococcus aureus (Photo courtesy of AIMPLAS)

Portable Biosensor Platform to Reduce Hospital-Acquired Infections

Approximately 4 million patients in the European Union acquire healthcare-associated infections (HAIs) or nosocomial infections each year, with around 37,000 deaths directly resulting from these infections,... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The acoustic pipette uses sound waves to test for biomarkers in blood (Photo courtesy of Patrick Campbell/CU Boulder)

Handheld, Sound-Based Diagnostic System Delivers Bedside Blood Test Results in An Hour

Patients who go to a doctor for a blood test often have to contend with a needle and syringe, followed by a long wait—sometimes hours or even days—for lab results. Scientists have been working hard to... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.