DEEP MOVEMENT: Deep learning of movie files for management of endovascular thrombectomy

OBJECTIVES: Treatment and outcomes of acute stroke have been revolutionised by mechanical thrombectomy. Deep learning has shown great promise in diagnostics but applications in video and interventional radiology lag behind. We aimed to develop a model that takes as input digital subtraction angiogra...

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Detalles Bibliográficos
Autores principales: Kelly, Brendan, Martinez, Mesha, Do, Huy, Hayden, Joel, Huang, Yuhao, Yedavalli, Vivek, Ho, Chang, Keane, Pearse A., Killeen, Ronan, Lawlor, Aonghus, Moseley, Michael E., Yeom, Kristen W., Lee, Edward H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Interventional
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10326097/
https://www.ncbi.nlm.nih.gov/pubmed/36847835
http://dx.doi.org/10.1007/s00330-023-09478-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10326097/
https://www.ncbi.nlm.nih.gov/pubmed/36847835
http://dx.doi.org/10.1007/s00330-023-09478-3

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