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A generative flow-based model for volumetric data augmentation in 3D deep learning for computed tomographic colonography
PURPOSE: Deep learning can be used for improving the performance of computer-aided detection (CADe) in various medical imaging tasks. However, in computed tomographic (CT) colonography, the performance is limited by the relatively small size and the variety of the available training datasets. Our pu...
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| Publicado no: | Int J Comput Assist Radiol Surg |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Springer International Publishing
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7822776/ https://ncbi.nlm.nih.gov/pubmed/33150471 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s11548-020-02275-z |
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