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

Download Mobile App




Low-Cost Whole-Body MRI Device Combined with AI Generates High-Quality Results

By MedImaging International staff writers
Posted on 10 May 2024
Image: Computing-powered whole-body MRI at 0.05 Tesla (Photo courtesy of Zhao, et al., doi: 10.1126/science.adm7168)
Image: Computing-powered whole-body MRI at 0.05 Tesla (Photo courtesy of Zhao, et al., doi: 10.1126/science.adm7168)

Magnetic Resonance Imaging (MRI) has significantly transformed healthcare, providing a noninvasive, radiation-free method for detailed imaging. It is especially promising for the future of medical diagnosis as it integrates with artificial intelligence (AI). Yet, after fifty years of development, MRI technology is still largely out of reach for many, particularly in low- and middle-income countries, mainly because of the prohibitive costs of standard superconducting MRI machines and the specialized infrastructure they require. These machines are typically located in specialized radiology departments or large imaging centers, which limits their presence in smaller healthcare facilities. Furthermore, the need for radiofrequency (RF)-shielded rooms and high power demands also restrict the broader adoption of MRI technology. Now, a new study has shown that machine learning can enable low-power MRI systems that are both cheaper and safe, without compromising on diagnostic accuracy.

The findings of the study by researchers at The University of Hong Kong (Hong Kong SAR, China) mark a significant step forward towards creating affordable, patient-oriented, and deep learning-enhanced ultra-low-field (ULF) MRI scanners. These innovations aim to fulfill the clinical needs unmet in various global healthcare environments. To overcome barriers to MRI access, the team designed a ULF MRI scanner that is both low-power and simplified for easier use. It operates off a standard wall outlet and does not require RF or magnetic shielding. This scanner utilizes a modest 0.05 Tesla (T) magnet—significantly less powerful than the typical 1.5 T to 7 T magnets found in most MRI devices—and employs active sensing combined with deep learning techniques to minimize electromagnetic interference and enhance image quality. Additionally, the device's power consumption is considerably lower during scans, using only 1800 watts (W), compared to the 25000 W or more required by traditional MRI systems. In tests conducted with healthy volunteers, the scanner successfully produced images that were as clear and detailed as those from higher-powered MRI systems currently in clinical use.

“Low-field MRI has yet to mature to enable cost-effective access to medical imaging,” stated the researchers. “Its potential as an essential and environmentally sustainable health technology will be proven when many communities around the world can use low-field MRI without barriers.”

Related Links:
The University of Hong Kong

Multi-Use Ultrasound Table
Clinton
Digital Color Doppler Ultrasound System
MS22Plus
Mammography System (Analog)
MAM VENUS
Computed Tomography System
Aquilion ONE / INSIGHT Edition

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.