Technology | March 06, 2013

Esaote Launches Improved Imaging Software for Ultrasound, MRI

March 6, 2013 — Esaote launched its next generation imaging technology for dedicated magnetic resonance imaging (MRI) and ultrasound. The eHD for ultrasound and eXP technology for dedicated MRI represent step-change innovations in the accuracy, quality, speed and flexibility of imaging technology.

“What we are launching today represents a complete re-thinking and re-engineering of our technologies in Dedicated MRI and Ultrasound,” said Claudio Buffagni — global marketing director at Esaote. “Our vision, investment and intense technical focus has enabled the realization of technology capable of serving the demands of medicine now and for another generation.”

eHD Ultrasound Technology

eHD is the culmination of a complete re-engineering process through the image capture, processing and display interfaces of Esaote’s MyLab ultrasound systems.  eHD represents a step-change in ultrasound diagnostic quality and flexibility.

At its core the eHD Technology features the eHD Pulser creating optimal ultrasound beam waveform for ultimate image clarity with no frame rate reduction. eHD has also been applied to Esaote’s iQProbe to improve transducer bandwidth and deliver increased signal sensitivity. An appleprobe’ grip configuration has also been introduced for greater operator control and comfort.

eHD features key software development to reduce interference and deliver better visibility of internal structures and improved readability and diagnosis. Esaote’s advanced Doppler technology has been updated with the introduction of eHD CFM, which offers optimized vessel border detection with increased sensitivity and depth. For high resolution, high definition work, eHD XFlow is available to maximize spatial resolution and Doppler signal penetration.

Inside every Esaote eHD Technology optimized system is an array of the latest visualization tools and technologies including Virtual Navigator and multi dimensional imaging capability, ensuring the very best diagnostic image is available to the operator in the most relevant format.

eXP MRI Technology

eXP musculoskeletal dedicated MRI system technology pushes Esaote’s systems faster with more accurate acquisition and reconstruction processing for improved image quality. Scan times are dramatically reduced, as are overall power consumption and running costs.

To increase the speed of image acquisition and reconstruction, eXP combines powerful GPU hardware with advanced software, producing superior quality images with substantially reduced scan times. For example, Fast Spin Echo (FSE) sequences can be obtained up to 40 percent faster with eXP Technology.

eXP features improved methods to manage the Echo Train Length combined with highly sophisticated algorithms for the acquisition and reconstruction of the K-space to improve diagnostic accuracy. Similarly, the use of Metallic Artefact Reduction (MAR) technique reduces artefacts and improves diagnostic quality when imaging patients with metallic implants.

eXP is available on the new G-Scan Brio and in the future could also be applied to other new systems or as an upgrade to existing systems, helping to protect investment and prolonging the useful life of existing installations.

For more information: www.esaote.com

Related Content

Artificial Intelligence Performs As Well As Experienced Radiologists in Detecting Prostate Cancer
News | Artificial Intelligence | April 18, 2019
University of California Los Angeles (UCLA) researchers have developed a new artificial intelligence (AI) system to...
Ebit and DiA Imaging Analysis Partner on AI-based Cardiac Ultrasound Analysis
News | Cardiovascular Ultrasound | April 16, 2019
DiA Imaging Analysis has partnered with the Italian healthcare IT company Ebit (Esaote Group), to offer DiA’s LVivo...
360 Photos | 360 View Photos | April 12, 2019
This 360 degree view shows staff at the ...
A smart algorithm has been trained on a neural network to recognize the appearance of breast cancer in MR images

A smart algorithm has been trained on a neural network to recognize the appearance of breast cancer in MR images. The algorithm, described at the SBI/ACR Breast Imaging Symposium, used “Deep Learning,“ a form of machine learning, which is a type of artificial intelligence. Graphic courtesy of Sarah Eskreis-Winkler, M.D.

Feature | Artificial Intelligence | April 12, 2019 | By Greg Freiherr
The use of smart algorithms has the potential to make healthcare more efficient.
DiA Imaging Analysis Introduces LVivo SAX Ultrasound Analysis Tool
Technology | Cardiovascular Ultrasound | April 09, 2019
DiA Imaging Analysis announced the launch of LVivo SAX, a cardiac analysis tool that helps clinicians quickly and...
SuperSonic Imagine Highlights Aixplorer Mach 30 Breast Ultrasound at SBI/ACR Breast Imaging Symposium
News | Ultrasound Women's Health | April 03, 2019
SuperSonic Imagine will introduce the new generation of its Aixplorer Mach 30 breast ultrasound solution at the 2019...
Videos | RSNA | April 03, 2019
ITN Editor Dave Fornell takes a tour of some of the most interesting new medical imaging technologies displa
NIH Study of Brain Energy Patterns Provides New Insights into Alcohol Effects

NIH scientists present a new method for combining measures of brain activity (left) and glucose consumption (right) to study regional specialization and to better understand the effects of alcohol on the human brain. Image courtesy of Ehsan Shokri-Kojori, Ph.D., of NIAAA.

News | Neuro Imaging | March 22, 2019
March 22, 2019 — Assessing the patterns of energy use and neuronal activity simultaneously in the human brain improve