Journal article

AutoDensity: an automated method to measure mammographic breast density that predicts breast cancer risk and screening

Carolyn Nickson, Yulia Arzhaeva, Zoe Aitken, Tarek Elgindy, Mitchell Buckley, Min Li, Dallas R English, Anne M Kavanagh

Breast Cancer Research | BMC | Published : 2013

Grants

Funding Acknowledgements

We thank BreastScreen Victoria for providing permission to use mammogram images and client data for the purpose of this study. At the Commonwealth Scientific and Industrial Research Organisation, we thank Ms Leanne Bischof of the Centre for Mathematics, Informatics and Statistics and Mr Jason Dowling of the Australian eHealth Research Centre for contributing to discussions on image processing, and Dr Olivier Salvado, Group Leader of Biomedical Imaging at the Australian eHealth Research Centre for supporting CSIRO involvement in this study, and Dr Pascal Vallotton, Group Leader of Quantitative Imaging at the Centre for Mathematics, Informatics and Statistics, for contributing staff time and existing image processing software resources to the study. This study was funded by the University of Melbourne Collaboration Grant 'A software platform for comparing automated breast density measurement techniques', the Victorian Breast Cancer Research Foundation Research Grant 'Molecular Determinants of Mammographic Density' and the National Breast Cancer Foundation Collaborative Grant 'Integration of BreastScreen with epidemiological, molecular and translational research program'.CN, ZA and ML were funded by the Victorian Breast Cancer Research Foundation Research Grant 'Molecular Determinants of Mammographic Density' and the National Breast Cancer Foundation Collaborative Grant 'Integration of BreastScreen with epidemiological, molecular and translational research program'. YA, TE and MB were funded by the Commonwealth Scientific and Industrial Research Organisation. AK was funded by the University of Melbourne and DE by the University of Melbourne and Cancer Council Victoria.