Accurate proton density estimations are required to obtain tissue volume fractions from multi-component MR Fingerprinting data. We propose a method for estimating relative proton densities per tissue while taking the receiver sensitivity profile into account. In 20 different numerical brain phantoms this shows to improve tissue segmentations compared to conventional methods that use $$$T_1$$$ weighted images. Estimated proton density values for single slice in vivo data (7 scans for 4 subjects) were in range with literature values in particular for white and gray matter.
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