Reliable skeletal segmentation of T1-weighted Dixon MRI is a first step towards measuring marrow fat-fraction as a surrogate metric for early marrow infiltration. We proposed an uncertainty-aware 2D U-Net (uU-Net) to reduce the impact of noisy ground-truth labels on segmentation accuracy. Five-fold cross-validation on a dataset of 30 myeloma patients provided a mean ± SD Dice coefficient of 0.74 ± 0.03 (vs. 0.73 ± 0.04, U-Net) and 0.63 ± 0.03 (vs 0.62 ± 0.04, U-Net) for pelvic and abdominal stations, respectively. Of clinical importance, improved segmentation of the ilium and vertebrae were achieved.
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