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Fully automated body composition analysis in routine CT imaging using 3D semantic segmentation convolutional neural networks
OBJECTIVES: Body tissue composition is a long-known biomarker with high diagnostic and prognostic value not only in cardiovascular, oncological, and orthopedic diseases but also in rehabilitation medicine or drug dosage. In this study, the aim was to develop a fully automated, reproducible, and quan...
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| Veröffentlicht in: | Eur Radiol |
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| Hauptverfasser: | , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Springer Berlin Heidelberg
2020
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7979624/ https://ncbi.nlm.nih.gov/pubmed/32945971 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00330-020-07147-3 |
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