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High throughput image labeling on chest computed tomography by deep learning
When mining image data from PACs or clinical trials or processing large volumes of data without curation, the relevant scans must be identified among irrelevant or redundant data. Only images acquired with appropriate technical factors, patient positioning, and physiological conditions may be applic...
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| Publicado no: | J Med Imaging (Bellingham) |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Society of Photo-Optical Instrumentation Engineers
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7082666/ https://ncbi.nlm.nih.gov/pubmed/32219151 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/1.JMI.7.2.024501 |
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