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Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
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High-resolution Structural Magnetic Resonance Imaging of the Human Subcortex In Vivo and Postmortem
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In-vivo imaging with a low-cost MRI scanner and cloud data processing in low-resource settings.

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    Researchers upgraded a low-cost, low-field MRI scanner in Africa, achieving clinically relevant brain imaging quality. This demonstrates the potential for accessible magnetic resonance imaging (MRI) in low-resource settings.

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    Area of Science:

    • Medical Imaging
    • Biophysics
    • Engineering

    Background:

    • Low-field magnetic resonance imaging (MRI) systems offer a potentially cost-effective solution for medical diagnostics in resource-limited settings.
    • Operational challenges, including electromagnetic noise and power instability, hinder the widespread adoption of MRI in low-resource environments.
    • Developing sustainable MRI technology requires addressing hardware limitations and optimizing software for challenging conditions.

    Purpose of the Study:

    • To showcase in-vivo imaging capabilities of a low-cost, low-field MRI scanner developed and operated in Africa.
    • To illustrate how targeted hardware and software enhancements can overcome operational limitations in low-resource settings.
    • To validate the feasibility of advanced MRI techniques on an upgraded, affordable system.

    Main Methods:

    • A 46 mT Halbach MRI scanner underwent significant upgrades, including improved grounding, shielding, and new control electronics with open-source software.
    • Noise performance was rigorously assessed using a standardized protocol.
    • Three-dimensional (3D) Rare-sequence brain imaging was performed, with distortion correction implemented via cloud-based reconstructions using magnetic field maps.

    Main Results:

    • The upgraded MRI system achieved noise levels significantly below the thermal limit, ensuring stable operation.
    • High-quality, 3D T1- and T2-weighted brain images were successfully acquired.
    • Distortion correction was effectively applied, with near real-time visualization enabled by remote GPU processing.

    Conclusions:

    • Clinically relevant MRI image quality is achievable with low-cost systems by effectively managing electromagnetic interference and power fluctuations.
    • This study confirms the viability of developing sustainable MRI technology in low-resource regions.
    • Future clinical translation hinges on ensuring stable power supply and fostering local expertise in MRI operation and maintenance.