Prediction of reader estimates of mammographic density using convolutional neural networks

Mammographic density is an important risk factor for breast cancer. In recent research, percentage density assessed visually using visual analogue scales (VAS) showed stronger risk prediction than existing automated density measures, suggesting readers may recognize relevant image features not yet c...

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Enregistré dans:
Détails bibliographiques
Publié dans:J Med Imaging (Bellingham)
Auteurs principaux: Ionescu, Georgia V., Fergie, Martin, Berks, Michael, Harkness, Elaine F., Hulleman, Johan, Brentnall, Adam R., Cuzick, Jack, Evans, D. Gareth, Astley, Susan M.
Format: Artigo
Langue:Inglês
Publié: Society of Photo-Optical Instrumentation Engineers 2019
Sujets:
Special Section on Advances in Breast Imaging
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC6357906/
https://ncbi.nlm.nih.gov/pubmed/30746393
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/1.JMI.6.3.031405
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