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Automated segmentation of lung, liver, and liver tumors from Tc‐99m MAA SPECT/CT images for Y‐90 radioembolization using convolutional neural networks
PURPOSE: (90)Y selective internal radiation therapy (SIRT) has become a safe and effective treatment option for liver cancer. However, segmentation of target and organ‐at‐risks is labor‐intensive and time‐consuming in (90)Y SIRT planning. In this study, we developed a convolutional neural network (C...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9298038/ https://www.ncbi.nlm.nih.gov/pubmed/34657293 http://dx.doi.org/10.1002/mp.15303 |