CBIS-DDSM [@lee_curated_2016] which contains images that are converted into the standard DICOM format. The dataset which consisted of 2478 mammography images from 1249 women was downloaded from the CBIS-DDSM website and included both craniocaudal (CC) and mediolateral oblique (MLO) views for most of the exams. Each view was treated as a separate image in this study due to the sample size limit. The purpose of this study was to predict the malignant vs. benign (or normal) status of each image. We performed an 85-15 split on the patient-level data to create independent training and test sets. In the training set, we further isolated 10% of the patients to create an independent validation set. The splits were done in a stratified fashion to maintain the same proportion of cancer cases in the training, validation and test sets. The total numbers of images in the training, validation and testing sets were: 1903, 199 and 376, respectively.

The DDSM database contains the pixel-level annotations for the ROIs and their pathologically confirmed labels: benign or malignant. It further labels each ROI as a calcification or mass. Most mammograms contain only one ROI. All mammograms were converted into PNG format and down-sized to $1152 \times 