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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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| Publicat a: | Sci Rep |
|---|---|
| Autors principals: | , , , , , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Nature Publishing Group UK
2020
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7652921/ https://ncbi.nlm.nih.gov/pubmed/33168895 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-020-76459-7 |
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