Curated Breast Imaging Subset of Digital Database for Screening Mammography (CBIS-DDSM)

This CBIS-DDSM (Curated Breast Imaging Subset of DDSM) is an updated and standardized version of the Digital Database for Screening Mammography (DDSM). The DDSM is a database of 2,620 scanned film mammography studies. It contains normal, benign, and malignant cases with verified pathology information. The scale of the database along with ground truth validation makes the DDSM a useful tool in the development and testing of decision support systems. The CBIS-DDSM collection includes a subset of the DDSM data selected and curated by a trained mammographer. The images have been decompressed and converted to DICOM format. Updated ROI segmentation and bounding boxes, and pathologic diagnosis for training data are also included. Published research results from work in developing decision support systems in mammography are difficult to replicate due to the lack of a standard evaluation data set; most computer-aided diagnosis (CADx) and detection (CADe) algorithms for breast cancer in mammography are evaluated on private data sets or on unspecified subsets of public databases. Few well-curated public datasets have been provided for the mammography community. These include the DDSM, the Mammographic Imaging Analysis Society (MIAS) database, and the Image Retrieval in Medical Applications (IRMA) project. Although these public data sets are useful, they are limited in terms of data set size and accessibility. For example, most researchers using the DDSM do not leverage all its images for a variety of historical reasons. When the database was released in 1997, computational resources to process hundreds or thousands of images were not widely available. Additionally, the DDSM images are saved in non-standard compression files that require the use of decompression code that has not been updated or maintained for modern computers. Finally, the ROI annotations for the abnormalities in the DDSM were provided to indicate a general position of lesions, but not a precise segmentation for them. Therefore, many researchers must implement segmentation algorithms for accurate feature extraction. This causes an inability to directly compare the performance of methods or to replicate prior results. The CBIS-DDSM collection addresses that challenge by publicly releasing an curated and standardized version of the DDSM for evaluation of future CADx and CADe systems (sometimes referred to generally as CAD) research in mammography.CBIS-DDSM（Curated Breast Imaging Subset of DDSM）是乳腺筛查影像数字数据库（Digital Database for Screening Mammography，简称DDSM）的更新标准化版本。DDSM是包含2620份扫描胶片乳腺摄影研究的数据库，涵盖经病理证实的正常、良性及恶性病例。该数据库规模庞大且附带真值验证，是开发和测试决策支持系统的实用工具。 CBIS-DDSM数据集由经过专业培训的乳腺影像医师从DDSM中精选并整理而成，所有影像均已解压缩并转换为DICOM格式。数据集还包含更新的感兴趣区（Region of Interest，ROI）分割标注、边界框信息，以及训练数据对应的病理诊断结果。 以往乳腺影像领域的决策支持系统研究成果难以复现，原因在于缺乏标准化的评估数据集——大多数乳腺癌计算机辅助诊断（Computer-aided Diagnosis，CADx）和计算机辅助检测（Computer-aided Detection，CADe）算法均在私有数据集或未明确说明的公共数据库子集上进行评估。目前面向乳腺影像领域的高质量公开数据集较为稀缺，现有公开数据集包括DDSM、乳腺影像分析学会（Mammographic Imaging Analysis Society，MIAS）数据库以及医学影像检索应用（Image Retrieval in Medical Applications，IRMA）项目。 尽管上述公开数据集具备一定实用价值，但在数据集规模和可访问性方面存在局限。例如，受诸多历史因素影响，多数使用DDSM的研究者并未充分利用其全部影像资源。1997年该数据库发布时，处理数百乃至数千幅影像的计算资源尚未普及；此外，DDSM影像采用非标准压缩格式存储，需要使用适配旧版环境的解压代码，无法在现代计算机上直接使用。更关键的是，DDSM中针对异常区域的ROI标注仅用于指示病灶的大致位置，并未提供精确的分割掩码，因此许多研究者不得不自行实现分割算法以完成特征提取，这导致不同方法的性能无法直接对比，也难以复现过往的研究结果。 CBIS-DDSM数据集正是为解决这一痛点而推出，它将经过精选和标准化处理的DDSM版本公开发布，用于评估未来乳腺影像领域的CADx、CADe（广义上也可统称为CAD）系统相关研究。