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FatSegNet: A Fully Automated Deep Learning Pipeline for Adipose Tissue Segmentation on Abdominal Dixon MRI
PURPOSE: Introduce and validate a novel, fast and fully automated deep learning pipeline (FatSegNet) to accurately identify, segment, and quantify visceral and subcutaneous adipose tissue (VAT and SAT) within a consistent, anatomically defined abdominal region on Dixon MRI scans. METHOD: FatSegNet i...
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| Publicado no: | Magn Reson Med |
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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/PMC6949410/ https://ncbi.nlm.nih.gov/pubmed/31631409 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/mrm.28022 |
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