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A novel deep learning architecture outperforming ‘off-the-shelf’ transfer learning and feature-based methods in the automated assessment of mammographic breast density
Potentially suspicious breast neoplasms could be masked by high tissue density, thus increasing the probability of a false-negative diagnosis. Furthermore, differentiating breast tissue type enables patient pre-screening stratification and risk assessment. In this study, we propose and evaluate adva...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
D.A. Spandidos
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6787954/ https://www.ncbi.nlm.nih.gov/pubmed/31545461 http://dx.doi.org/10.3892/or.2019.7312 |