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

Download Mobile App




Automated Brain MRI Image Labeling Holds Enormous Potential for AI

By HospiMedica International staff writers
Posted on 06 Aug 2021
Print article
Illustration
Illustration
Researchers have automated brain MRI image labeling, needed to teach machine learning image recognition models, by deriving important labels from radiology reports and accurately assigning them to the corresponding MRI examinations, allowing more than 100,00 MRI examinations to be labeled in less than half an hour.

This was the first study that allowed researchers at King's College London (London UK) to label complex MRI image datasets at scale. The researchers say it would take years to manually perform labelling of more than 100,000 MRI examinations. Deep learning typically requires tens of thousands of labelled images to achieve the best possible performance in image recognition tasks. This represents a bottleneck to the development of deep learning systems for complex image datasets, particularly MRI which is fundamental to neurological abnormality detection.

"By overcoming this bottleneck, we have massively facilitated future deep learning image recognition tasks and this will almost certainly accelerate the arrival into the clinic of automated brain MRI readers. The potential for patient benefit through, ultimately, timely diagnosis, is enormous," said senior author, Dr. Tom Booth from the School of Biomedical Engineering & Imaging Sciences at King's College London.

"This study builds on recent breakthroughs in natural language processing, particularly the release of large transformer-based models such as BERT and BioBERT which have been trained on huge collections of unlabeled text such as all of English Wikipedia, and all PubMed Central abstracts and full-text articles; in the spirit of open-access science, we have also made our code and models available to other researchers to ensure that as many people benefit from this work as possible," added lead author, Dr. David Wood from the School of Biomedical Engineering & Imaging Sciences.

According to the researchers, while one barrier has now been overcome, further challenges will be, firstly, to perform the deep learning image recognition tasks which also have multiple technical challenges; and secondly, once this is achieved, to ensure the developed models can still perform accurately across different hospitals using different scanners.

Related Links:

King's College London

Gold Member
12-Channel ECG
CM1200B
Gold Member
Disposable Protective Suit For Medical Use
Disposable Protective Suit For Medical Use
Silver Member
Wireless Mobile ECG Recorder
NR-1207-3/NR-1207-E
New
Vital Signs Monitor
Aurus 10

Print article

Channels

Critical Care

view channel
Image: Researchers have developed an advanced shear-thinning hydrogel for aneurysm repair (Photo courtesy of TIBI)

New Hydrogel Features Enhanced Capabilities for Treating Aneurysms and Halting Progression

Aneurysms can develop in blood vessels in different body areas, often as a result of atherosclerosis, infections, inflammatory diseases, and other risk factors. These conditions lead to chronic inflammation,... Read more

Surgical Techniques

view channel
Image: The living replacement knee will be tested in clinical trials within five years (Photo courtesy of ARPA-H)

Living Knee Replacement to Revolutionize Osteoarthritis Treatment

Osteoarthritis is the most prevalent type of arthritis, characterized by the progressive deterioration of cartilage, or the protective tissue covering the bone ends, resulting in pain, stiffness, and impaired... Read more

Patient Care

view channel
Image: The newly-launched solution can transform operating room scheduling and boost utilization rates (Photo courtesy of Fujitsu)

Surgical Capacity Optimization Solution Helps Hospitals Boost OR Utilization

An innovative solution has the capability to transform surgical capacity utilization by targeting the root cause of surgical block time inefficiencies. Fujitsu Limited’s (Tokyo, Japan) Surgical Capacity... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The new eye-safe laser technology can diagnose traumatic brain injury (Photo courtesy of 123RF)

Novel Diagnostic Hand-Held Device Detects Known Biomarkers for Traumatic Brain Injury

The growing need for prompt and efficient diagnosis of traumatic brain injury (TBI), a major cause of mortality globally, has spurred the development of innovative diagnostic technologies.... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.