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.

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Example of artificial intelligence generated measurements to quantify the size of a lung cancer nodule during a followup CT scan to see if the lesion is regressing with treatment. This type of automation can aid radiologists by doing the tedious, time consuming work. Photo by Dave Fornell

8 trends in radiology technology to watch in 2023

Here is a list of some key trends in radiology technology from our editors based on our coverage of the radiology market.

How EHR 'choice architecture' for imaging could be wasting time and money

When choosing and implementing an electronic health record system, it is important to consider how the system’s architecture might affect providers’ decision-making. 

Lack of transparency in AI research limits reproducibility, renders work 'worthless'

A recent analysis found that a significant amount of studies do not provide information pertaining to their raw data, source code or model. As a result, up to 97% of these studies do not produce systems that are fit to be used in real-world clinical scenarios. 

An example of artificial intelligence (AI) automated detection of a intracranial hemorrhage (ICH) in. a CT scan used to send alerts to the stroke acute care team before a radiologist even sees the exam. Example shown by TeraRecon at RSNA 2022.

VIDEO: Radiology AI aids acute care and other departments

Sanjay Parekh, PhD, senior market analyst with Signify Research, explains how some radiology AI is being adopted outside of radiology departments to improve care.

Example of AI automated detection and highlighting of critical lung findings on a chest X-ray for a possible lung cancer nodule and fibrosis. Example shown by AI vendor Lunit.

VIDEO: Radiology AI trends at RSNA 2022

Sanjay Parekh, PhD, senior market analyst with Signify Research, discusses trends in radiology AI seen on the expo floor and in sessions at RSNA 2022.

What do Google and Amazon really want from medical imaging?

Big Tech’s recent expansions into medical imaging have business watchers scrambling to decipher the unspoken stratagems beneath the conspicuous moves.

Dynamic lung air flow analysis just using X-ray without any contrast with new technology from 4D Medical.

PHOTO GALLERY: New technology and trends at RSNA 2022

Images from the Radiological Society of North America (RSNA) 2022 annual meeting Nov. 27- Dec. 1 in Chicago. The gallery includes new technologies and a look at sights around the world's largest radiology conference. 

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Google Health partners with iCAD in commercial AI imaging push

The deal is the first commercial partnership for Google Health to introduce its breast imaging AI into clinical practice.

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