Fully automated accurate patient positioning in computed tomography using anterior–posterior localizer images and a deep neural network: a dual-center study

OBJECTIVES: This study aimed to improve patient positioning accuracy by relying on a CT localizer and a deep neural network to optimize image quality and radiation dose. METHODS: We included 5754 chest CT axial and anterior–posterior (AP) images from two different centers, C1 and C2. After pre-proce...

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Detalles Bibliográficos
Autores principales: Salimi, Yazdan, Shiri, Isaac, Akavanallaf, Azadeh, Mansouri, Zahra, Arabi, Hossein, Zaidi, Habib
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Computed Tomography
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9879741/
https://www.ncbi.nlm.nih.gov/pubmed/36703015
http://dx.doi.org/10.1007/s00330-023-09424-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9879741/
https://www.ncbi.nlm.nih.gov/pubmed/36703015
http://dx.doi.org/10.1007/s00330-023-09424-3

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