Labeling cells with 19F nanoparticles (NPs) continues to elicit interest for non-invasive localization of inflammation and monitoring immune cell therapy. Systematic overestimation in low SNR MRI of 19F-NPs has been previously described which needs to be corrected for valid quantitative conclusions. We develop a statistical model which successfully compensates this bias and demonstrate its efficacy for the correct estimation of signal intensities on neuroinflammation data acquired in a mouse model of multiple sclerosis. The correction only relies on the image data itself and promises to be a valuable contribution to the development of reliable quantitative 19F MRI.
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