Enterprise Imaging

Enterprise imaging brings together all imaging exams, patient data and reports from across a healthcare system into one location to aid efficiency and economy of scale for data storage. This enables immediate access to images and reports any clinical user of the electronic medical record (EMR) across a healthcare system, regardless of location. Enterprise imaging (EI) systems replace the former system of using a variety of disparate, siloed picture archiving and communication systems (PACS), radiology information systems (RIS), and a variety of separate, dedicated workstations and logins to view or post-process different imaging modalities. Often these siloed systems cannot interoperate and cannot easily be connected. Web-based EI systems are becoming the standard across most healthcare systems to incorporate not only radiology, but also cardiology (CVIS), pathology and dozens of other departments to centralize all patient data into one cloud-based data storage and data management system.

AI company to develop radiology-specific LLM reporting assistant
The system will assist radiologists by identifying lesions and drafting a single-sentence, localization-aware report alerting readers to the finding.
Cardiovascular IT systems keep evolving with AI, Epic integration on the rise
A Signify Research representative highlights key trends in cardiovascular IT systems, including the growing role of AI and much more.
5 takeaways from new ACR, Society for Imaging Informatics in Medicine cybersecurity guidance
The two recently convened a panel of multidisciplinary stakeholders to discuss this issue, including radiologists, technologists, informaticists and physicists.
Join our live webinar on Wednesday: Data migration lessons from the University of California, San Francisco
Enterprise Imaging experts will share advice in a Radiology Business webinar Aug. 13, exploring how they’re tackling the task of migrating over 1.6M imaging files after a large-scale acquisition.
GPT-4o translates radiology reports written in different languages in less than 30 seconds
These findings could have positive implications for regions with diverse patient populations, authors of a new analysis suggest.

AI company to develop radiology-specific LLM reporting assistant

The system will assist radiologists by identifying lesions and drafting a single-sentence, localization-aware report alerting readers to the finding.

Healthcare IT analyst Amy Thompson from Signify Research explains trends in cardiology information systems at ACC 2025.

Cardiovascular IT systems keep evolving with AI, Epic integration on the rise

A Signify Research representative highlights key trends in cardiovascular IT systems, including the growing role of AI and much more.

cybersecurity hacker ransomware cyber data breach

5 takeaways from new ACR, Society for Imaging Informatics in Medicine cybersecurity guidance

The two recently convened a panel of multidisciplinary stakeholders to discuss this issue, including radiologists, technologists, informaticists and physicists.

data migration file transfer enterprise imaging

Join our live webinar on Wednesday: Data migration lessons from the University of California, San Francisco

Enterprise Imaging experts will share advice in a Radiology Business webinar Aug. 13, exploring how they’re tackling the task of migrating over 1.6M imaging files after a large-scale acquisition.

GPT-4o translates radiology reports written in different languages in less than 30 seconds

These findings could have positive implications for regions with diverse patient populations, authors of a new analysis suggest.

Radiology cyberattack exposes data from hundreds of thousands of patients in Washington

The incident happened in January of this year, with attackers gaining access to the practice’s systems for five days before they were shut out.

Large language models outperform physicians at imaging modality selection, study shows

New findings highlight the “remarkable potential” of these artificial intelligence tools in improving radiology workflows.

Network peer to peer P2P learning web communication interoperability

Hospital system catches 70% of lung cancer cases in earliest stage, thanks to AI intervention

The solution was developed to be adaptable within the EHR, enabling improved communication of incidental findings beyond just pulmonary nodules to include other high-risk findings.