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itations of CT-based approaches, benefiting patients who are sensitive to radiation from CT.Supplemental material is available for this article.© RSNA, 2020. To automate skeletal muscle segmentation in a pediatric population using convolutional neural networks that identify and segment the L3 level at CT. In this retrospective study, two sets of U-Net-based models were developed to identify the L3 level in the sagittal plane and segment the skeletal muscle from the corresponding axial image. For model development, 370 patients (sampled
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