News | Ultrasound Imaging | July 26, 2019

Intelligent Ultrasound Group Collaborating With the National Imaging Academy Wales

Welsh collaboration to develop leading-edge artificial intelligence-based ultrasound tools for diagnostic imaging

Intelligent Ultrasound Group Collaborating With the National Imaging Academy Wales

The ScanTrainer transvaginal simulator is one example of Intelligent Ultrasound's simulation technologies.

July 26, 2019 — Artificial intelligence (AI)-based ultrasound software and simulation company Intelligent Ultrasound Group plc (AIM: MED) has entered a collaboration with the National Imaging Academy Wales (NIAW) to develop AI tools to aid ultrasound scanning and enhance ultrasound education.

Both located in South Wales, NIAW and Intelligent Ultrasound share a common desire to improve ultrasound practice through education, innovation and research that will lead to improved clinical technique and as a result, improved patient care and outcomes.

Intelligent Ultrasound aims to make ultrasound easier for clinicians to use: For the clinic, it is developing real-time artificial intelligence-based clinical ultrasound image analysis software to improve scan quality and workflow; for the training room it manufactures advanced ultrasound training simulators to improve OBGYN, echocardiography and point-of-care sonography education. The company recently announced the signing of its first long-term licensing and co-development agreement with one of the world’s leading ultrasound equipment manufacturers to install its AI real-time image analysis software onto a range of specialty specific ultrasound systems marketed in the global healthcare market. More than 800 of Intelligent Ultrasound’s ScanTrainer, HeartWorks and BodyWorks Eve ultrasound simulators have been sold around the world, including to NIAW and other U.K. radiology academies to increase training opportunities. 

National Imaging Academy Wales opened in August 2018, funded by Welsh Government and NHS Wales to help address significant challenges across the diagnostic imaging workforce, enabling increased training capacity for radiologists in the first instance. As part of NHS Wales, NIAW provides comprehensive specialty training across all radiology imaging modalities including ultrasound, and is committed to training, collaboration, innovation and research. National Imaging Academy Wales is already a hub for diagnostic imaging in Wales and is progressing with developments to enhance radiology training and research.

This collaboration will combine Intelligent Ultrasound and NIAW’s complementary skills both to develop clinically relevant AI tools for the clinic and to improve ultrasound education by evaluating real-world simulator performance.

Phillip Wardle, M.D., NIAW director and consultant radiologist, said: “Working closer together, we both aim to develop simulation training and advanced deep-learning AI in ultrasound that will address the needs of current and future imaging workforce including sonographers and radiologists. By combining NIAW’s clinical expertise with Intelligent Ultrasound’s leading-edge in AI techniques and Simulation, we intend to help trainees in ultrasound to become proficient more quickly.”

For more information: www.intelligentultrasound.com

Related Content

Varian Unveils Ethos Solution for Adaptive Radiation Therapy
News | Image Guided Radiation Therapy (IGRT) | September 16, 2019
At the 2019 American Society for Radiation Oncology (ASTRO) annual meeting, being held Sept. 15-18 in Chicago, Varian...
FDA Clears GE Healthcare's Critical Care Suite Chest X-ray AI
Technology | X-Ray | September 12, 2019
GE Healthcare announced the U.S. Food and Drug Administration’s (FDA) 510(k) clearance of Critical Care Suite, a...
iCAD's ProFound AI Wins Best New Radiology Solution in 2019 MedTech Breakthrough Awards
News | Computer-Aided Detection Software | September 09, 2019
iCAD Inc. announced MedTech Breakthrough, an independent organization that recognizes the top companies and solutions...
Imaging Biometrics and Medical College of Wisconsin Awarded NIH Grant
News | Neuro Imaging | September 09, 2019
Imaging Biometrics LLC (IB), in collaboration with the Medical College of Wisconsin (MCW), has received a $2.75 million...
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. Image courtesy of Sarah Eskreis-Winkler, M.D.

Feature | Society of Breast Imaging (SBI) | September 06, 2019 | By Greg Freiherr
The use of smart algorithms has the potential to make healthcare more efficient.
Philips and Fujifilm booths at SIIM 2019.

Philips and Fujifilm booths at SIIM 2019.

Feature | SIIM | September 06, 2019 | By Greg Freiherr
Pragmatism from cybersecurity to enterprise imaging was in vogue at the 2019 meeting of the Society of Imaging Inform
Sudhen Desai, M.D.

Sudhen Desai, M.D.

Feature | Pediatric Imaging | September 04, 2019 | By Jeff Zagoudis
Burnout has become a popular buzzword in today’s business world, meant to describe prolonged periods of stress in the
Global Diagnostics Australia Incorporates AI Into Radiology Applications
News | Artificial Intelligence | September 04, 2019
Global Diagnostics Australia (GDA), a subsidiary of the Integral Diagnostics Group (IDX), has adopted artificial...
Medical Imaging Rates Continue to Rise Despite Push to Reduce Their Use
News | Radiology Imaging | September 03, 2019
Despite a broad campaign among physician groups to reduce the amount of medical imaging, use rates of various scans...
New Radiomics Model Uses Immunohistochemistry to Predict Thyroid Nodules

Workflow of radiomics analysis for IHC indicators. Yellow lines denote area of analysis; red lines denote ROI for radiomic features extraction. X = original image, L = low-pass filter, H = high-pass filter. Image courtesy of Jiabing Gu, et al.

News | Artificial Intelligence | September 03, 2019
Researchers have validated a first-of-its-kind machine learning–based model to evaluate immunohistochemical (IHC)...