LegSegNet is the first public end-to-end deep learning system for lower extremity CT tissue segmentation and body composition quantification, reporting an average Dice score of 89.31 on held-out test slices.
How to select slices for annotation to train best-performing deep learning segmentation models for cross-sectional med- ical images?arXiv preprint arXiv:2412.08081, 2024
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LegSegNet: A Public Deep Learning System for Lower Extremity CT Tissue Segmentation and Quantification
LegSegNet is the first public end-to-end deep learning system for lower extremity CT tissue segmentation and body composition quantification, reporting an average Dice score of 89.31 on held-out test slices.