Automated detection of IVC filters on radiographs with deep convolutional neural networks

PURPOSE: To create an algorithm able to accurately detect IVC filters on radiographs without human assistance, capable of being used to screen radiographs to identify patients needing IVC filter retrieval. METHODS: A primary dataset of 5225 images, 30% of which included IVC filters, was assembled an...

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Detalles Bibliográficos
Autores principales: Mongan, John, Kohli, Marc D., Houshyar, Roozbeh, Chang, Peter D., Glavis-Bloom, Justin, Taylor, Andrew G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Interventional Radiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9902407/
https://www.ncbi.nlm.nih.gov/pubmed/36371471
http://dx.doi.org/10.1007/s00261-022-03734-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9902407/
https://www.ncbi.nlm.nih.gov/pubmed/36371471
http://dx.doi.org/10.1007/s00261-022-03734-8

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