公开乳腺筛查影像数据集，助力自动化诊断研究
Full Field Digital Mammography Dataset from a Population Screening Program
- 源自加拿大省级筛查项目，含5997例四视图乳腺影像
- 每例均有活检确认，标注了放射科医生误判的假阳性案例
- 适合医学影像自动化、乳腺癌筛查算法研发人员使用
乳腺癌是全球女性第二大癌症风险。早期检测已被证明能有效降低死亡率。人群筛查项目定期为参与者安排乳腺钼靶检查，以促进早期发现。目前此类筛查仍依赖人工阅片，读片过程中的假阳性结果会导致不必要的随访检查和患者焦虑。自动化方法有望提升读片效率、一致性和准确性。为推动该技术发展，已有多个数据集被构建。本文针对人群筛查场景，推出来自加拿大某省筛查项目的NL-Breast-Screening数据集。该数据集包含5997个乳腺钼靶检查实例，每个均包含四个标准视角，并经活检证实。其中放射科医生误判的假阳性病例也已标注。NL-Breast数据集已公开，旨在推动人群筛查自动化技术的发展。
原文摘要 · Abstract (English)
Breast cancer presents the second largest cancer risk in the world to women. Early detection of cancer has been shown to be effective in reducing mortality. Population screening programs schedule regular mammography imaging for participants, promoting early detection. Currently, such screening programs require manual reading. False-positive errors in the reading process unnecessarily leads to costly follow-up and patient anxiety. Automated methods promise to provide more efficient, consistent and effective reading. To facilitate their development, a number of datasets have been created. With the aim of specifically targeting population screening programs, we introduce NL-Breast-Screening, a dataset from a Canadian provincial screening program. The dataset consists of 5997 mammography exams, each of which has four standard views and is biopsy-confirmed. Cases where radiologist reading was a false-positive are identified. NL-Breast is made publicly available as a new resource to promote advances in automation for population screening programs.
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