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Using convolutional neural networks for enhanced capture of breast parenchymal complexity patterns associated with breast cancer risk
RATIONALE AND OBJECTIVES: We evaluate utilizing convolutional neural networks (CNNs) to optimally fuse parenchymal complexity measurements generated by texture analysis into discriminative meta-features relevant for breast cancer risk prediction. MATERIALS AND METHODS: With IRB approval and HIPAA co...
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| Pubblicato in: | Acad Radiol |
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| Autori principali: | , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2018
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6026048/ https://ncbi.nlm.nih.gov/pubmed/29395798 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.acra.2017.12.025 |
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