A novel and fully automated mammographic texture analysis for risk prediction: results from two case-control studies

BACKGROUND: The percentage of mammographic dense tissue (PD) is an important risk factor for breast cancer, and there is some evidence that texture features may further improve predictive ability. However, relatively little work has assessed or validated textural feature algorithms using raw full fi...

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Detalles Bibliográficos
Autores principales: Wang, Chao, Brentnall, Adam R., Cuzick, Jack, Harkness, Elaine F., Evans, D. Gareth, Astley, Susan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5648465/
https://www.ncbi.nlm.nih.gov/pubmed/29047382
http://dx.doi.org/10.1186/s13058-017-0906-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5648465/
https://www.ncbi.nlm.nih.gov/pubmed/29047382
http://dx.doi.org/10.1186/s13058-017-0906-6

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