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Deep learning for automated segmentation of pelvic muscles, fat and bone from CT studies for body composition assessment
OBJECTIVE: To develop a deep convolutional neural network (CNN) to automatically segment an axial CT image of the pelvis for body composition measures. We hypothesized that a deep CNN approach would achieve high accuracy when compared to manual segmentations as the reference standard. MATERIAL AND M...
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| Publicado no: | Skeletal Radiol |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6980503/ https://ncbi.nlm.nih.gov/pubmed/31396667 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00256-019-03289-8 |
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