Keywords: Low-Field MRI, Brain, ultra-low-field MRI, point-of-care MRIThe high cost of clinical MRI has severely limited its accessibility in many regions. Ultra-low-field (ULF) MRI systems have been developed to address this issue, providing diagnostic imaging at a significantly lower cost. However, computational tools that are used for clinical scans are often not applicable to ULF images which suffer from both SNR and resolution loss. Here, we compare two approaches for improving the resolution of ULF images and two techniques for extracting volumetric information from each approach. We show that given effective post-processing, ULF images can capture expected age-related volumetric changes in the brain.
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