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 hp
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




New Model Makes MRI More Accurate and Reliable

By MedImaging International staff writers
Posted on 30 Dec 2024
Image: The new MRI model can produce more accurate and reliable analysis of brain structures (Photo courtesy of 123RF)
Image: The new MRI model can produce more accurate and reliable analysis of brain structures (Photo courtesy of 123RF)

Magnetic resonance imaging (MRI) is a leading technology for examining the internal structures of the human brain. This non-invasive imaging technique uses a magnetic field and radio waves to capture images of soft tissues without involving radiation. However, MRI does have some limitations. Movements by the participant, such as blinking, breathing, or other involuntary actions, can cause image blurring and lead to ghost artifacts, which repeat the structures. This can be particularly challenging for children who find it difficult to remain still throughout the scan. As MRI is crucial for diagnosing brain conditions and conducting neurological research, maintaining high image quality is essential. Now, a new MRI model offers enhanced accuracy and reliability for brain structure analysis.

To address these issues and improve brain MRI image quality, researchers at the UNC School of Medicine (Chapel Hill, NC, USA) have developed the Brain MRI Enhancement foundation (BME-X), a model designed to correct motion, improve resolution, reduce noise, and enhance image contrast. A standout feature of this model is its ability to "harmonize" MRI images from various scanners. With many different MRI scanners in use across clinical settings, each with its own imaging parameters, achieving consistent results can be difficult. BME-X can integrate this data and standardize it, providing “harmonized” images suitable for both clinical and research purposes.

In a study published in Nature Biomedical Engineering, the BME-X model was tested using over 13,000 images from diverse patient groups and scanner types. The researchers found that BME-X outperformed other leading methods in addressing body motion, reconstructing high-resolution images from lower-resolution data, reducing noise, and managing pathological MRIs. The model’s strength in harmonizing data positions it to streamline clinical trials and research involving multiple institutions, while also contributing to the development of new, standardized neuroimaging protocols and procedures.

“Imaging quality is important for visualizing brain anatomy and pathology and can help inform clinical decisions,” said Li Wang, PhD, associate professor of radiology. “Our model can perform more accurate and reliable analysis of brain structures, which is critical for early detection, diagnosis, and monitoring of neurological conditions.”

Multi-Use Ultrasound Table
Clinton
Digital Radiographic System
OMNERA 300M
MRI System
nanoScan MRI 3T/7T
X-Ray Illuminator
X-Ray Viewbox Illuminators

Channels

Nuclear Medicine

view channel
Image: The new tracer, 64Cu-NOTA-EV-F(ab′)2​, targets nectin-4, a protein strongly linked to tumor growth in both TNBC and UBC cancer types. (Wenpeng Huang et al., DOI: 10.2967/jnumed.125.270132)

PET Tracer Enables Same-Day Imaging of Triple-Negative Breast and Urothelial Cancers

Triple-negative breast cancer (TNBC) and urothelial bladder carcinoma (UBC) are aggressive cancers often diagnosed at advanced stages, leaving limited time for effective treatment decisions.... Read more

General/Advanced Imaging

view channel
Image: Concept of the photo-thermoresponsive SCNPs (J F Thümmler et al., Commun Chem (2025). DOI: 10.1038/s42004-025-01518-x)

New Ultrasmall, Light-Sensitive Nanoparticles Could Serve as Contrast Agents

Medical imaging technologies face ongoing challenges in capturing accurate, detailed views of internal processes, especially in conditions like cancer, where tracking disease development and treatment... 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
Copyright © 2000-2025 Globetech Media. All rights reserved.