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...
| 主要な著者: | , , , , , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
SpringerOpen
2021-11-01
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| シリーズ: | EJNMMI Physics |
| 主題: | |
| オンライン･アクセス: | https://doi.org/10.1186/s40658-021-00424-0 |