Keywords: Bone, Fat
Chemical Shift Encoded (CSE) MRI method has been used to highlight subregional differences in the femoral bone marrow in terms of fatty acids composition in proximal femur, suggesting an important role of the marrow in bone quality. This method requires a certain number of echoes (3 for fat/water separation and >8 for fatty acids mapping). Deep Learning (DL) has been recently applied to accelerate, improve the quality and efficiency for fat/water separation in CSE-MRI. Our aim was to develop a DL-CSE method and evaluate it for fatty acids composition mapping; using different echo numbers.
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