Deep Learning–Assisted Diagnosis of Cerebral Aneurysms Using the HeadXNet Model

IMPORTANCE: Deep learning has the potential to augment clinician performance in medical imaging interpretation and reduce time to diagnosis through automated segmentation. Few studies to date have explored this topic. OBJECTIVE: To develop and apply a neural network segmentation model (the HeadXNet...

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Detalhes bibliográficos
Publicado no:JAMA Netw Open
Main Authors: Park, Allison, Chute, Chris, Rajpurkar, Pranav, Lou, Joe, Ball, Robyn L., Shpanskaya, Katie, Jabarkheel, Rashad, Kim, Lily H., McKenna, Emily, Tseng, Joe, Ni, Jason, Wishah, Fidaa, Wittber, Fred, Hong, David S., Wilson, Thomas J., Halabi, Safwan, Basu, Sanjay, Patel, Bhavik N., Lungren, Matthew P., Ng, Andrew Y., Yeom, Kristen W.
Formato: Artigo
Idioma:Inglês
Publicado em: American Medical Association 2019
Assuntos:
Original Investigation
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6563570/
https://ncbi.nlm.nih.gov/pubmed/31173130
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1001/jamanetworkopen.2019.5600
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