Fully automated identification of brain abnormality from whole-body FDG-PET imaging using deep learning-based brain extraction and statistical parametric mapping
Abstract Background The whole brain is often covered in [18F]Fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) in oncology patients, but the covered brain abnormality is typically screened by visual interpretation without quantitative analysis in clinical practice. In this study, we aim...
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Auteurs principaux: | , , , , , |
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Format: | article |
Langue: | EN |
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SpringerOpen
2021
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Accès en ligne: | https://doaj.org/article/a28bd4daf3b3432e8414859dba25bda2 |
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