Keywords: Low-Field MRI, Low-Field MRI, open-source, console, acquisition
Motivation: We challenge proprietary barriers in low-field MRI to enhance methodological integration. Our focus is on improving system versatility for advanced imaging.
Goal(s): To create a versatile, MRI console driven by open-source software, capable of integrating sophisticated low-field imaging techniques. This involves for instance additional sensors or real-time adaptions.
Approach: We implemented Spectrum-Instrumentation measurement cards with a high-performance reconstruction system. The open-source Python software, incorporating a Pulseq interpreter, allows to streamline flexible, fast, and transparent low-field imaging applications.
Results: Successful implementation evidenced by high-fidelity Pulseq sequence execution to image 3D printed brain phantoms on a system capable of in-vivo applications.
Impact: The open and versatile design of our proposed console paves the way for advanced techniques in low-field MRI, enabling widespread adoption in research facilities and fostering innovative MRI applications in resource-limited settings.
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