Imaging Informatics

Imaging informatics (also known as radiology informatics, a component of wider medical or healthcare informatics) includes systems to transfer images and radiology data between radiologists, referring physicians, patients and the entire enterprise. This includes picture archiving and communication systems (PACS), wider enterprise image systems, radiology information. systems (RIS), connections to share data with the electronic medical record (EMR), and software to enable advanced visualization, reporting, artificial intelligence (AI) applications, analytics, exam ordering, clinical decision support, dictation, and remote image sharing and viewing systems.

SimonMed

Radiology practice SimonMed Imaging suffers apparent ransomware attack

Hacker group Medusa claimed responsibility for the cyberattack on its blog, according to a report published Tuesday. 

Top performing PACS companies based on user feedback

Agfa and Sectra both performed well with end-user satisfaction scores in the 2025 Best in KLAS list of radiology IT systems.

Video of Tim Kearns explaining the new Konica Minolta Exa Enterprise imaging system released at RSNA 2024.

Enterprise imaging expands in smaller and midsized hospitals

Smaller health systems are increasingly moving into this realm. Tim Kearns, director of marketing and healthcare IT, Konica Minolta Imaging USA, explains the implications.

 

Nina Kottler, MD, Radiology Partners, offers overview of the U.S. AI regulatory landscape as government and radiologists work on ways to ensure artificial intelligence is not bias and works properly.

Overview of the regulatory landscape of AI in radiology

Nina Kottler, MD, associate CMO for clinical AI at Radiology Partners, explains the movement toward greater regulation of artificial intelligence and the need to test for bias. 

Medical imaging trends to watch in 2025

The healthcare market analysis firm Signify Research released a list of predictions in radiology its analysts expect to see in 2025. 

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Automated tracking helps leave no incidental finding behind

Radiology researchers have developed and validated an automated program for tracking incidental imaging findings. The system facilitates communications between radiologists, patients and primary care providers whenever such findings turn up.  

Video of Steve Rankin, chief strategy officer for Enlitic, explaining how AI can help standardize labeling of medical images.

AI can help radiology standardize image exam data labeling

To fully leverage today's radiology IT systems, standardization is a necessity. Steve Rankin, chief strategy officer for Enlitic, explains how artificial intelligence can help.

Video Christoph Wald explains how the Health AI Challenge help understand how foundational AI models work

ACR partners to create AI foundational model assessment website

Christoph Wald, MD, vice chair of the American College of Radiology Board of Chancellors, explains the partnerships with academic institutions to create the Health AI Challenge will help provide a better understanding of how foundational AI models work.

 

Around the web

The ACR hopes these changes, including the addition of diagnostic performance feedback, will help reduce the number of patients with incidental nodules lost to follow-up each year.

And it can do so with almost 100% accuracy as a first reader, according to a new large-scale analysis.

The patient, who was being cared for in the ICU, was not accompanied or monitored by nursing staff during his exam, despite being sedated.