Intelerad is now a GE HealthCare company. Learn more about this partnership.
Our technology spans the patient journey to streamline processes and connect physicians, no matter where they are.
Transitioning medical imaging to the cloud—or adopting a hybrid approach—offers healthcare organizations scalability, cost savings, disaster recovery, and operational flexibility, making it a strategic move for long-term success.
Cloud adoption reduces IT burden, improves disaster recovery, and enables elastic scalability. Facilities can start with hybrid models—keeping some systems on-premise while migrating backups and archiving to the cloud—and later transition fully for maximum cost savings and flexibility.
Intelerad Cloud is a suite of tailored solutions for medical imaging facilities, including:
One Intelerad client saved USD 1.26 million over four years by moving from on-premise PACS to Intelerad Private Cloud. This client processes 800K+ studies annually, expects 10–15% growth, and operates 55+ radiology centers with full disaster recovery failover.
Related: Benefits and disadvantages of cloud versus onsite PACS
Cloud adoption is ideal for:
Intelerad offers:
If your medical imaging facility seeks a cloud evolution partner, have a look at Intelerad Cloud solutions. Book a demo today with our sales team!
Enterprise image exchange enables healthcare organizations to securely share and access medical images across systems, facilities, and networks. Learn how enterprise image exchange platforms support interoperability, secure image sharing, and scalable imaging workflows across healthcare organizations.
Image sharing in radiology still falls short because most systems are designed to move files, not deliver images within clinical workflows at the moment they’re needed. This blog explores why image sharing feels broken, what’s changing in radiology image access, and how time-to-image is becoming a more meaningful way to evaluate performance.
Radiology workflows often break down due to disconnected systems, manual processes, and inconsistent data across case selection, prior access, reporting, and communication. These challenges can interrupt reading flow, delay diagnosis, and create inefficiencies across the entire imaging process.