A fast and fully-automated deep-learning approach for accurate hemorrhage segmentation and volume quantification in non-contrast whole-head CT

This project aimed to develop and evaluate a fast and fully-automated deep-learning method applying convolutional neural networks with deep supervision (CNN-DS) for accurate hematoma segmentation and volume quantification in computed tomography (CT) scans. Non-contrast whole-head CT scans of 55 pati...

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Detalles Bibliográficos
Autores principales: Arab, Ali, Chinda, Betty, Medvedev, George, Siu, William, Guo, Hui, Gu, Tao, Moreno, Sylvain, Hamarneh, Ghassan, Ester, Martin, Song, Xiaowei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652921/
https://www.ncbi.nlm.nih.gov/pubmed/33168895
http://dx.doi.org/10.1038/s41598-020-76459-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652921/
https://www.ncbi.nlm.nih.gov/pubmed/33168895
http://dx.doi.org/10.1038/s41598-020-76459-7

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