A convolutional neural network-based system to prevent patient misidentification in FDG-PET examinations

Patient misidentification in imaging examinations has become a serious problem in clinical settings. Such misidentification could be prevented if patient characteristics such as sex, age, and body weight could be predicted based on an image of the patient, with an alert issued when a mismatch betwee...

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Detalles Bibliográficos
Autores principales: Kawauchi, Keisuke, Hirata, Kenji, Katoh, Chietsugu, Ichikawa, Seiya, Manabe, Osamu, Kobayashi, Kentaro, Watanabe, Shiro, Furuya, Sho, Shiga, Tohru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510755/
https://www.ncbi.nlm.nih.gov/pubmed/31076620
http://dx.doi.org/10.1038/s41598-019-43656-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510755/
https://www.ncbi.nlm.nih.gov/pubmed/31076620
http://dx.doi.org/10.1038/s41598-019-43656-y

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