Deep Learning-based Quantification of Abdominal Subcutaneous and Visceral Fat Volume on CT Images

RATIONALE AND OBJECTIVES: Develop a deep learning-based algorithm using the U-Net architecture to measure abdominal fat on computed tomography (CT) images. MATERIALS AND METHODS: Sequential CT images spanning the abdominal region of seven subjects were manually segmented to calculate subcutaneous fa...

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Detalhes bibliográficos
Publicado no:Acad Radiol
Main Authors: Grainger, Andrew T., Krishnaraj, Arun, Quinones, Michael H., Tustison, Nicholas J., Epstein, Samantha, Fuller, Daniela, Jha, Aakash, Allman, Kevin L., Shi, Weibin
Formato: Artigo
Idioma:Inglês
Publicado em: 2020
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7862413/
https://ncbi.nlm.nih.gov/pubmed/32771313
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.acra.2020.07.010
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