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.

SimonMed Imaging gives official notice of cyberattack weeks after initial reports
The Scottsdale, Arizona-based radiology practice issued a notice to impacted parties on March 28 after reports of the hack first started surfacing in mid-February.
RamSoft and Alpha Nodus partner to streamline imaging prior authorization processes
RamSoft, a leader in cloud-based RIS/PACS radiology solutions, and Alpha Nodus, a developer of AI-driven administrative tools for medical offices, announced their partnership on Wednesday.
FBI issues alert on notorious ransomware group that targeted radiology practice
Medusa has hacked over 300 victims including SimonMed Imaging, hospitals, law firms and manufacturers, according to the federal cybersecurity advisory.
MRI-based Node-RADS effectively improves staging of head and neck cancer
Use of the scoring system could offer providers valuable preoperative insight and help guide them in surgical decisions.
What radiologists think about using ChatGPT and AI in breast imaging
Manisha Bahl, MD, explained that ChatGPT and other large language models offer significant potential to help radiologists with breast imaging exams, but they are "not quite ready for primetime."

chatgpt artificial intelligence healthcare

How do radiologists feel about utilizing GPT-4 in practice?

In recent years, there has been much talk of the potential for large language models to improve radiology workflows.

AI-based 3D CTA reconstruction solution scores FDA clearance

Using the new solution, CTA recons are completed in a matter of minutes, not hours.

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.

GPT-4 helps ensure recommendations for additional imaging aren't overlooked in reports

Recommendations for additional imaging are routinely included in radiology reports but are sometimes overlooked or not communicated in a timely manner. Experts believe large language models can help address these lapses in care.

GPT-4 can proofread radiology reports for a penny apiece

Researchers estimate that it could cost less than $0.01 per report to use the large language model as a radiology report proofreader.

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.

radiology reporting EHR health record CDS AUC

How a health system automatically integrates AI results into radiology reports

The University of Pennsylvania in Philadelphia has aimed to tackle this conundrum, developing a deep learning-based image analysis tool and AI “orchestrator.”

Enterprise Imaging

SimonMed Imaging gives official notice of cyberattack weeks after initial reports

RamSoft and Alpha Nodus partner to streamline imaging prior authorization processes

FBI issues alert on notorious ransomware group that targeted radiology practice

MRI-based Node-RADS effectively improves staging of head and neck cancer

What radiologists think about using ChatGPT and AI in breast imaging