Good news! This could be a game changer!
Probably many people do not realize how expensive MRI machines are: They cost about $1 million and about $15,000 per month in maintenance.
"... As a result, despite their utility, MRIs are hardly affordable. Every hospital in the world needs at least one, but 2 in 3 people worldwide have limited or no MRI access. ...
The total number of clinical scanners is only about 50,000 in the entire world. ...
The MRI prototype developed by Wu and colleagues operates at 0.055 Teslas, much lower than existing commercial units. ...
The total number of clinical scanners is only about 50,000 in the entire world. ...
The MRI prototype developed by Wu and colleagues operates at 0.055 Teslas, much lower than existing commercial units. ...
The shielding part is particularly exciting. Normally, MRIs need the shielding to eliminate interference (for instance, with other electronic devices) — but researchers managed to eliminate the need for shielding by using a deep learning algorithm, ...:
“Our innovations encompass three aspects: (i) we eliminated the bulky RF shielding room requirement through deep learning, thus the MRI scan can now be made in open space; (ii) we implemented and demonstrated the feasibility of key and widely adopted clinical brain imaging protocols on this low-cost platform, which were previously believed challenging if not impossible at very low field and on low-cost hardware platforms; and (iii) we performed preliminary clinical study and validated results by directly comparing to 3T results.” ..."
From the abstract:
"... There are approximately seven scanners per million inhabitants and over 90% are concentrated in high-income countries. We describe an ultra-low-field brain MRI scanner that operates using a standard AC power outlet and is low cost to build. Using a permanent 0.055 Tesla Samarium-cobalt magnet and deep learning for cancellation of electromagnetic interference, it requires neither magnetic nor radiofrequency shielding cages. The scanner is compact, mobile, and acoustically quiet during scanning. We implement four standard clinical neuroimaging protocols (T1- and T2-weighted, fluid-attenuated inversion recovery like, and diffusion-weighted imaging) on this system, and demonstrate preliminary feasibility in diagnosing brain tumor and stroke. Such technology has the potential to meet clinical needs at point of care or in low and middle income countries."
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