Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network

OBJECTIVES: To evaluate the performance of a novel three-dimensional (3D) joint convolutional and recurrent neural network (CNN-RNN) for the detection of intracranial hemorrhage (ICH) and its five subtypes (cerebral parenchymal, intraventricular, subdural, epidural, and subarachnoid) in non-contrast...

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Detalles Bibliográficos
Autores principales: Ye, Hai, Gao, Feng, Yin, Youbing, Guo, Danfeng, Zhao, Pengfei, Lu, Yi, Wang, Xin, Bai, Junjie, Cao, Kunlin, Song, Qi, Zhang, Heye, Chen, Wei, Guo, Xuejun, Xia, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2019
Materias:
Imaging Informatics and Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6795911/
https://www.ncbi.nlm.nih.gov/pubmed/31041565
http://dx.doi.org/10.1007/s00330-019-06163-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6795911/
https://www.ncbi.nlm.nih.gov/pubmed/31041565
http://dx.doi.org/10.1007/s00330-019-06163-2

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