VinDr-Mammo: A large-scale benchmark dataset for computer-aided detection and diagnosis in full-field digital mammography

Breast cancer is one of the most prevalent types of cancer and the leading type of cancer death. Mammography is the recommended imaging modality for periodic breast cancer screening. A few datasets have been published to develop computer-aided tools for mammography analysis. However, these datasets either have a limited sample size or consist of screen-film mammography (SFM), which have been replaced by full-field digital mammography (FFDM) in clinical practices. This project introduces a large-scale full-field digital mammography dataset of 5,000 four-view exams, which are double read by experienced mammographers to provide cancer assessment and breast density following the Breast Imaging Report and Data System (BI-RADS). Breast abnormalities that require further examination are also marked by bounding rectangles.

乳腺癌乃最常见的癌症类型之一，亦为癌症死亡的主要原因。乳腺摄影是推荐用于定期乳腺筛查的影像学检查方法。目前已有少数数据集被发布，旨在开发用于乳腺摄影分析的计算机辅助工具。然而，这些数据集要么样本量有限，要么由屏-片式乳腺摄影（SFM）组成，而屏-片式乳腺摄影已被临床实践中的全视野数字乳腺摄影（FFDM）所取代。本项目引入了一个包含5,000份四视图检查的大规模全视野数字乳腺摄影数据集，由经验丰富的乳腺摄影专家进行双重阅读，以提供基于乳腺影像报告和数据系统（BI-RADS）的癌症评估和乳腺密度评估。需要进一步检查的乳腺异常也通过边界矩形进行标记。