Ultra-low-dose chest CT imaging of COVID-19 patients using a deep residual neural network

OBJECTIVES: The current study aimed to design an ultra-low-dose CT examination protocol using a deep learning approach suitable for clinical diagnosis of COVID-19 patients. METHODS: In this study, 800, 170, and 171 pairs of ultra-low-dose and full-dose CT images were used as input/output as training...

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Detalles Bibliográficos
Autores principales: Shiri, Isaac, Akhavanallaf, Azadeh, Sanaat, Amirhossein, Salimi, Yazdan, Askari, Dariush, Mansouri, Zahra, Shayesteh, Sajad P., Hasanian, Mohammad, Rezaei-Kalantari, Kiara, Salahshour, Ali, Sandoughdaran, Saleh, Abdollahi, Hamid, Arabi, Hossein, Zaidi, Habib
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Computed Tomography
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7467843/
https://www.ncbi.nlm.nih.gov/pubmed/32879987
http://dx.doi.org/10.1007/s00330-020-07225-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7467843/
https://www.ncbi.nlm.nih.gov/pubmed/32879987
http://dx.doi.org/10.1007/s00330-020-07225-6

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