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.

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NLP shows ability to extract measurements, core descriptors from radiology reports

Natural language processing (NLP) has shown potential to extract measurements and their primary descriptors from radiology reports and provide them in a structured format, according to findings published in the Journal of Digital Imaging.

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More big imaging data, radiomics key to personalized therapy for head and neck carcinomas

A new CT- and PET-imaging-based approach—one that entails applying big data to personalizing treatment protocols—is needed to better identify which head and neck carcinoma (HNC) patient subgroups respond to which specific therapies.

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How Secure Is That Scanner?

In a world of networked medical devices, it’s not hard to imagine a radiology-heavy cyberattack that is not only malicious but also ingenious.
 

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Signed, Sealed and Soon to be Delivered

Consolidation has become the name of the game for many private radiology practices, but not everyone wants in. Many unaffiliated groups still prefer the independent side of the playing field, defending their turf by contracting to provide imaging services to hospitals and health systems.

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NLP able to audit radiology reports, ID crucial information

Natural language processing (NLP) can provide significant value by auditing all communications related to critical findings, according to a new study published in the Journal of the American College of Radiology.

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AI extracts additional information, context from radiology reports

Machine learning (ML) can help providers extract all relevant facts from radiology reports in real time, according to a new study published in the Journal of Digital Imaging.

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Can radiologists rely on US LI-RADS for diagnosing HCC?

A recent study validating the 2017 version of the ultrasound Liver Imaging Reporting and Data System (US LI-RADS) for detecting hepatocellular carcinoma (HCC) identified a few limitations in its scoring.

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How technologists can save radiologists valuable time

Technologists can provide significant value by assigning protocols for certain CT and MRI examinations, according to a new study published in the American Journal of Roentgenology.

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