Fluorine-19 MRI has emerged as a promising tool for in vivo cell tracking, yet low achievable signal-to-noise ratios remain a major challenge. Compressed sensing offers increased sensitivity at the cost of introducing signal intensity bias. We show that at low signal levels the quantification performance of compressed sensing is similar to conventional methods due to signal intensity distribution induced bias effects, which also affect the Fourier reconstruction. To improve quantification results, we propose an intensity correction scheme based on ex vivo reference data.
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