Summary

This dataset consists of images from the DDSM and CBIS-DDSM datasets. The images have been pre-processed and converted to 299x299 images by extracting the ROIs.

The dataset contains 55,890 training examples, of which 14% are positive and the remaining 86% negative.

Pre-processing

The dataset consists of negative images from the DDSM dataset and positive images from the CBIS-DDSM dataset. The data was pre-processed to convert it into 299x299 images.

The negative (DDSM) images were tiled into 598x598 tiles, which were then resized to 299x299.

The positive (CBIS-DDSM) images had their ROIs extracted using the masks with a small amount of padding to provide context. Each ROI was then randomly cropped three times into 598x598 images, with random flips and rotations, and then the images were resized down to 299x299.