Automated mammographic measures that predict breast cancer risk

预测乳腺癌风险的自动化乳房X光检查措施

• 批准号: nhmrc : 1010644
• 负责人: Dr Carmel Apicella
• 金额: $ 27.09万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: NHMRC Project Grants
• 财政年份: 2011
• 资助国家: 澳大利亚
• 起止时间: 2011-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://researchdata.edu.au/automated-mammographic-measures-cancer-risk/109511
• 关键词: Automated; mammographic; measures; predict; breast

Mammographic density (MD) is one of the strongest predictors of breast cancer risk but its impractical measurement prevents its use in a clinical setting. An automated measure of MD would allow screening programs to identify and target women at higher risk of breast cancer which could lead to earlier diagnoses and better breast cancer outcomes. We aim to develop an automated measurement, maximized by its ability to predict breast cancer risk, and applicable to both film and digital mammograms.

乳腺摄影密度（MD）是乳腺癌风险最强的预测因子之一，但其不切实际的测量方法阻碍了其在临床环境中的使用。MD的自动测量将允许筛查计划识别和针对乳腺癌风险较高的女性，这可能导致早期诊断和更好的乳腺癌结果。我们的目标是开发一种自动化的测量方法，最大限度地提高其预测乳腺癌风险的能力，并适用于胶片和数字乳房X光检查。