Anomaly detection in chest (18)F-FDG PET/CT by Bayesian deep learning

PURPOSE: To develop an anomaly detection system in PET/CT with the tracer (18)F-fluorodeoxyglucose (FDG) that requires only normal PET/CT images for training and can detect abnormal FDG uptake at any location in the chest region. MATERIALS AND METHODS: We trained our model based on a Bayesian deep l...

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Detalles Bibliográficos
Autores principales: Nakao, Takahiro, Hanaoka, Shouhei, Nomura, Yukihiro, Hayashi, Naoto, Abe, Osamu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252947/
https://www.ncbi.nlm.nih.gov/pubmed/35094221
http://dx.doi.org/10.1007/s11604-022-01249-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252947/
https://www.ncbi.nlm.nih.gov/pubmed/35094221
http://dx.doi.org/10.1007/s11604-022-01249-2

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