Deep learning assistance increases the detection sensitivity of radiologists for secondary intracranial aneurysms in subarachnoid hemorrhage

PURPOSE: To evaluate whether a deep learning model (DLM) could increase the detection sensitivity of radiologists for intracranial aneurysms on CT angiography (CTA) in aneurysmal subarachnoid hemorrhage (aSAH). METHODS: Three different DLMs were trained on CTA datasets of 68 aSAH patients with 79 an...

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Detalles Bibliográficos
Autores principales: Pennig, Lenhard, Hoyer, Ulrike Cornelia Isabel, Krauskopf, Alexandra, Shahzad, Rahil, Jünger, Stephanie T., Thiele, Frank, Laukamp, Kai Roman, Grunz, Jan-Peter, Perkuhn, Michael, Schlamann, Marc, Kabbasch, Christoph, Borggrefe, Jan, Goertz, Lukas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Diagnostic Neuroradiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8589782/
https://www.ncbi.nlm.nih.gov/pubmed/33837806
http://dx.doi.org/10.1007/s00234-021-02697-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8589782/
https://www.ncbi.nlm.nih.gov/pubmed/33837806
http://dx.doi.org/10.1007/s00234-021-02697-9

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