Quantitative magnetic resonance imaging can monitor intramuscular fat accumulation and has proven value for follow-up and therapy evaluation of neuromuscular disease. So far, segmentation processes of individual muscles from quantitative MRI data have been recognized as challenging in healthy subjects and even more challenging in patients for whom borders between muscles can be compromised by the disease process. We designed a semi-automatic segmentation pipeline of individual leg muscles in MR images based on automatic propagation of a minimal number of manually segmented MR slices. This segmentation pipeline allows an accurate follow-up of any MRI biomarkers in neuromuscular disorders.
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