Robustly segmenting quadriceps muscles of ultra-endurance athletes with weakly supervised U-Net
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classification
eess.IV
keywords
segmentationathletesmulti-atlasquadricepssupervisedu-netultra-enduranceweakly
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In this study, segmentation of quadriceps muscle heads of ultra-endurance athletes was done using a multi-atlas segmentation and corrective leaning framework where the registration based multi-atlas segmentation step was replaced with weakly supervised U-Net. For the case with remarkably different morphology, our method produced improved accuracy, while reduced significantly the computation time.
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