Exploring the potential performance of 0.2 T low-field unshielded MRI scanner using deep learning techniques

Objective Using deep learning-based techniques to overcome physical limitations and explore the potential performance of 0.2 T low-field unshielded MRI in terms of imaging quality and speed. Methods First, fast and high-quality unshielded imaging is achieved using active electromagnetic shielding an...

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Bibliographic Details
Published in:Magma (New York, N.Y.) Vol. 38; no. 2; pp. 253 - 269
Main Authors: Li, Lei, He, Qingyuan, Wei, Shufeng, Wang, Huixian, Wang, Zheng, Yang, Wenhui
Format: Journal Article
Language:English
Published: Cham Springer International Publishing 01.04.2025
Subjects:
Algorithms
Basic Science - Reconstruction algorithms and artificial intelligence
Biomedical Engineering and Bioengineering
Computer Appl. in Life Sciences
Deep Learning
Equipment Design
Health Informatics
Humans
Image Processing, Computer-Assisted - methods
Imaging
Magnetic Resonance Imaging - instrumentation
Magnetic Resonance Imaging - methods
Medicine
Medicine & Public Health
Phantoms, Imaging
Radiology
Research Article
Signal-To-Noise Ratio
Solid State Physics
Low-field MRI
Deep learning
Super-resolution
Cross-field
Image processing
ISSN:1352-8661, 1352-8661
Online Access:Get full text
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Summary:Objective Using deep learning-based techniques to overcome physical limitations and explore the potential performance of 0.2 T low-field unshielded MRI in terms of imaging quality and speed. Methods First, fast and high-quality unshielded imaging is achieved using active electromagnetic shielding and basic super-resolution. Then, the speed of basic super-resolution imaging is further improved by reducing the number of excitations. Next, the feasibility of using cross-field super-resolution to map low-field low-resolution images to high-field ultra-high-resolution images is analyzed. Finally, by cascading basic and cross-field super-resolution, the quality of the low-field low-resolution image is improved to the level of the high-field ultra-high-resolution image. Results Under unshielded conditions, our 0.2 T scanner can achieve image quality comparable to that of a 1.5 T scanner (acquisition resolution of 512 × 512, spatial resolution of 0.45 mm 2 ), and a single-orientation imaging time of less than 3.3 min. Discussion The proposed strategy overcomes the physical limitations of the hardware and rapidly acquires images close to the high-field level on a low-field unshielded MRI scanner. These findings have significant practical implications for the advances in MRI technology, supporting the shift from conventional scanners to point-of-care imaging systems.
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ISSN:1352-8661
1352-8661
DOI:10.1007/s10334-025-01234-6