Israel-based Zebra Medical Vision has unveiled a new algorithm for detecting compression and other vertebral fractures.
Part of the firm’s Deep Learning Imaging Analytics platform, the new algorithm will automatically identify and localize compression fractures.
Zebra vertebral compression fracture (VCF) algorithm will apply deep learning to differentiate between compression fractures and more ubiquitous degenerative endplate changes and osteophytes.
The algorithm will enable healthcare providers to identify people at risk and place them under supervision or fracture prevention to decrease the risks of subsequent osteoporotic fractures.
It will also be provided on the firm’s Profound platform, which enables users to upload their imaging scans and security automated insights regarding their imaging data.
The company also produces algorithms to detect low bone mineral density, breast cancer, fatty liver, coronary artery calcium, emphysema and others.
According to the company, the diagnosing of VCFs will enable to implement both primary therapeutic and secondary preventative interventions.
The company also produces algorithms to detect low bone mineral density, breast cancer, fatty liver, coronary artery calcium, emphysema and others.
Zebra Medical Vision co-founder and CEO Elad Benjamin said: “Osteoporotic fractures have a deeply negative impact on the lives of patients and their caregivers.
“Implementation of our VCF algorithm can help prevent a large number of these fractures – allowing for better preventative and overall care, as well as reducing long term healthcare costs for providers.”
Image: Zebra Medical Vision’s new algorithm will help to detect vertebral fractures. Photo: courtesy of zebra-med, shutterstock.