We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




World’s First Online Image-Based COVID-19 Diagnosis Improvement Tool Launched

By MedImaging International staff writers
Posted on 03 Apr 2020
Print article
Image: DetectED-X platform (Photo courtesy of DetectED-X)
Image: DetectED-X platform (Photo courtesy of DetectED-X)
DetectED-X (Sydney, Australia), a University of Sydney spinoff comprising radiation and imaging experts, has launched the world’s only online image-based COVID-19 diagnosis improvement tool for healthcare workers. The start-up has directed its breast cancer diagnosis tool at the coronavirus, drawing on pandemic cases globally with support from healthcare and industry leaders to ramp up COVID-19 detection. DetectED-X’s CovED platform, which can be accessed anywhere with an internet connection, is being provided for free and is supported by healthcare experts and leading corporations globally.

DetectED-X’s CovED follows on from the highly successful BreastScreen Reader Assessment Strategy (BREAST) platform, created in 2010 at the University of Sydney, which has been used internationally including in the US and Europe. The cloud-based life-saving technology can help doctors and radiologists diagnose cases faster and more accurately. Computed tomography (CT) lung scans, which produce cross-sectional images using X-rays and computers, are typically used after swabs are taken, to identify the extent and location of the disease; the CT scans produce images within minutes and are also able to diagnose COVID-19 in the very early stages that escape detection with nucleic acid tests.

DetectED-X’s approach, which includes algorithms to improve radiologist skills and identifying where errors were made on images in the online training sessions, has been shown to improve results significantly. Through CovED, individual clinicians can assess their performance on images on screen, and receive immediate feedback, including performance scores used in the industry. The image files personalized for each clinician are instantly returned showing any errors in their virtual diagnosis and the difficulty level is increased over time. As COVID-19 testing ramps up, the platform could facilitate rapid training where required – with modules able to be completed in as little as an hour – upskilling staff unfamiliar with lung radiology to prepare standardized reports for expert review.

“Our platform does not replace expert medical and radiologic training but CovED provides an effective way to recognize rapidly the appearances of COVID-19, which could be critical in a situation of too many patients and not enough expert radiologists, with the modules taking just 1-2 hours to complete,” said CEO Professor Patrick Brennan, medical radiation scientist and educator from the University of Sydney School of Health Sciences, Faculty of Medicine and Health. “This will be immediately crucial in developing countries, where numbers of radiologists are often insufficient – our tests will help people not only diagnose COVID-19 but also identify potentially life-threatening cases wherever they are.”

Related Links:
DetectED-X

Gold Member
Solid State Kv/Dose Multi-Sensor
AGMS-DM+
New
Ultrasound Needle Guide
Ultra-Pro II
New
Thyroid Shield
Standard Thyroid Shield
Oncology Information System
RayCare

Print article

Channels

Radiography

view channel
:	Image: The AI model could be a valuable adjunct to human radiologists in breast cancer diagnoses and risk prediction (Photo courtesy of 123RF)

AI Model Predicts 5-Year Breast Cancer Risk from Mammograms

Approximately 13% of U.S. women, or one in every eight, are predicted to develop invasive breast cancer over their lifetime, with 1 in 39 women (3%) succumbing to the illness, according to the American... Read more

Nuclear Medicine

view channel
Image: The AI system uses scintigraphy imaging for early diagnosis of cardiac amyloidosis (Photo courtesy of 123RF)

AI System Automatically and Reliably Detects Cardiac Amyloidosis Using Scintigraphy Imaging

Cardiac amyloidosis, a condition characterized by the buildup of abnormal protein deposits (amyloids) in the heart muscle, severely affects heart function and can lead to heart failure or death without... Read more

General/Advanced Imaging

view channel
Image: The CIARTIC Move self-driving mobile C-arm has received FDA clearance (Photo courtesy of Siemens)

Self-Driving Mobile C-Arm Reduces Imaging Time during Surgery

Intraoperative imaging faces significant challenges due to staff shortages and the high demands placed on surgical teams in the operating room (OR). A common challenge during many OR procedures is the... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more

Industry News

view channel
Image: Samsung Medison CEO Mr. Yongkwan Kim and Bracco Imaging CEO Dr. Fulvio Renoldi Bracco endorsed a MoU agreement (Photo courtesy of Bracco Group)

Samsung and Bracco Enter Into New Diagnostic Ultrasound Technology Agreement

Samsung Medison (Seoul, South Korea) and Bracco Imaging (Milan, Italy) have entered into a Memorandum of Understanding (MoU) agreement to pioneer a new area for diagnostic ultrasound devices and contrast agents.... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.