A novel and fully automated mammographic texture analysis for risk prediction: results from two case-control studies
Author:
Funder
Cancer Research UK
Programme Grants for Applied Research
Genesis Prevention Appeal
Publisher
Springer Science and Business Media LLC
Link
http://link.springer.com/content/pdf/10.1186/s13058-017-0906-6.pdf
Reference32 articles.
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3. Li J, Szekely L, Eriksson L, Heddson B, Sundbom A, Czene K, et al. High-throughput mammographic-density measurement: a tool for risk prediction of breast cancer. Breast Cancer Res. 2012;14:R114.
4. Keller BM, Nathan DL, Wang Y, Zheng YJ, Gee JC, Conant EF, et al. Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation. Med Phys. 2012;39:4903–17.
5. Wolfe JN. Breast patterns as an index of risk for developing breast cancer. Am J Roentgenol. 1976;126:1130–9.
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