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
PURITAN MEDICAL

Download Mobile App





Automatic AI-Based Diagnosis Framework Enables Detection of COVID-19 from Chest X-Ray Images

By HospiMedica International staff writers
Posted on 13 Jan 2022
Print article
Illustration
Illustration

A novel machine learning framework could alleviate the work of radiologists by providing fast and accurate diagnosis of COVID-19 from chest X-ray images.

A team of scientists at Incheon National University (Incheon, Korea) has developed an automatic COVID-19 diagnosis framework that turns things up a notch by combining two powerful artificial intelligence (AI)-based techniques. Their system can be trained to accurately differentiate between chest X-ray images of COVID-19 patients from non-COVID-19 ones.

Several studies have reported that AI-based systems can be used to detect COVID-19 in chest X-ray images because the disease tends to produce areas with pus and water in the lungs, which show up as white spots in the X-ray scans. Although various diagnostic AI models based on this principle have been proposed, improving their accuracy, speed, and applicability remains a top priority.

The scientists developed the new COVID-19 detection system by combining the two algorithms Faster R-CNN and ResNet-101. The first one is a machine learning-based model that uses a region-proposal network, which can be trained to identify the relevant regions in an input image. The second one is a deep-learning neural network comprising 101 layers, which was used as a backbone. ResNet-101, when trained with enough input data, is a powerful model for image recognition.

The scientists believe that their strategy could prove useful for the early detection of COVID-19 in hospitals and public health centers. Using automatic diagnostic techniques based on AI technology could take some work and pressure off of radiologists and other medical experts, who have been facing huge workloads since the pandemic started. Moreover, as more modern medical devices become connected to the Internet, it will be possible to feed vast amounts of training data to the proposed model; this will result in even higher accuracies, and not just for COVID-19.

"To the best of our knowledge, our approach is the first to combine ResNet-101 and Faster R-CNN for COVID-19 detection," said Professor Gwanggil Jeon of Incheon National University who led the team. "After training our model with 8800 X-ray images, we obtained a remarkable accuracy of 98%."

"The deep learning approach used in our study are applicable to other types of medical images and could be used to diagnose different diseases," added Prof. Jeon.

Related Links:
Incheon National University 


Print article
IIR Middle East

Channels

Critical Care

view channel
Image: Three dimensional measurement of the all-mesh thermistor (Photo courtesy of Shinshu University)

Ultraflexible, Gas-Permeable Thermistors to Pave Way for On-Skin Medical Sensors and Implantable Devices

On-skin medical sensors and wearable health devices are important health care tools that must be incredibly flexible and ultrathin so they can move with the human body. In addition, the technology has... Read more

Surgical Techniques

view channel
Image: Engineers have developed a process that enables soft robots to grow like plants (Photo courtesy of University of Minnesota)

Soft Robotic System Can Grow Like Plants to Allow Surgical Access to Hard-To-Reach Areas

Soft robotics is an emerging field where robots are made of soft, pliable materials as opposed to rigid ones. Soft growing robots can create new material and “grow” as they move. These machines could be... Read more

Patient Care

view channel
Image: The biomolecular film can be picked up with tweezers and placed onto a wound (Photo courtesy of TUM)

Biomolecular Wound Healing Film Adheres to Sensitive Tissue and Releases Active Ingredients

Conventional bandages may be very effective for treating smaller skin abrasions, but things get more difficult when it comes to soft-tissue injuries such as on the tongue or on sensitive surfaces like... Read more

Health IT

view channel
Image: Using digital data can improve health outcomes (Photo courtesy of Unsplash)

Electronic Health Records May Be Key to Improving Patient Care, Study Finds

When a patient gets transferred from a hospital to a nearby specialist or rehabilitation facility, it is often difficult for personnel at the new facility to access the patient’s electronic health records... Read more

Business

view channel
Image: Differentiated stapling technology for bariatric surgery (Photo courtesy of Standard Bariatrics)

Teleflex Completes Acquisition of Bariatric Stapling Technology Innovator

Teleflex Incorporated (Wayne, PA, USA), a leading global provider of medical technologies, has completed the previously announced acquisition of Standard Bariatrics, Inc. (Cincinnati, OH, USA), which has... Read more
Copyright © 2000-2022 Globetech Media. All rights reserved.