A new 21-inch clinical review display offers a 40% higher digital imaging and communications in medicine (DICOM) calibrated luminance, and almost twice the contrast ratio of the previous generation.
The Eonis 21” display offers a full-screen format, with a traditional 4:3 aspect ratio and a 2MP resolution for viewing consistent, quality-controlled images. The monitor features light emitting diode (LED) backlights to deliver a brightness of 250 cd/m², as well as an excellent contrast ratio of 1,500:1 for viewing high-detail images quickly, efficiently, and with fewer image manipulations. In-Plane Switching (IPS) technology ensures accurate image display, allowing users to angle the display according to their own preference.
Built-in ambient light presets ensure perfect image quality in dark or bright viewing environments. Additionally, thanks to a front-of-screen consistency sensor which automatically aligns image quality every time the display is switched on, image reliability is maintained over time. Additional features include flexible tilt and swivel capabilities, making viewing more ergonomic. For example, positioning the display in portrait orientation provides radiologists with more flexibility when viewing skeletal radiography images or patient data.
And like all of the Eonis displays, the Eonis 21” comes with the MediCal QAWeb online service for quality assurance and remote asset management to provide healthcare specialists with consistent image quality, and healthcare information technology (IT) professionals with powerful management tools for controlling their clinical display fleet centrally. The Eonis 21” display and the the MediCal QAWeb online service are products of Barco (Kortrijk, Belgium).
“Eonis 21” is the perfect display for image review in radiology and cardiology,” said Geert Carrein, VP for strategic marketing at Barco. “Also, Eonis 21” comes with a unique front consistency sensor to guarantee consistent images over time and offers a 40% higher calibrated luminance, making it ideal for viewing standard PACS mages, RIS data, and image-enabled EMR.”