Automated identification of proton spectral characteristics has potential utility in accurate spectral fat saturation, improving dynamic shim routines, and optimizing bandwidth of radiofrequency pulses used in multi-slice or multi-band excitation. In this work, we present an algorithm for automated identification of fat and water proton spectral characteristics and evaluate its performance in 30 proton spectra from breast (number of subjects: n=20), ankle (n=11), and knee (n=9) anatomical regions.
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