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A large dataset of dynamic contrast-enhanced magnetic resonance images of the breast for breast cancer patients. Tumors annotated by radiologists. Extensive meta-data including patient demographics, treatment, outcomes, pathology, genomics.

This dataset is the dataset used in the following paper:

The dataset contains four components: (1) DICOM Images, (2) Annotation_Boxes, (3) Clinical_and_Other_Features, and (4) Imaging_Features.

(1) DICOM Images
Breast MRI images of 922 patients, inside the folder of each patient there are the following sequences: fat saturated pre-contrast sequence, fat saturated post-contrast sequences, and non-fat saturated T1 weighted sequence.

(2) Annotation_Boxes
Tumor annotations in the form of boxes drawn by radiologists, six values in the spreadsheet represent the location of the start row, end row, start column, end column, start slice, and end slice of the box. The annotation boxes
can be applied directly to pre and post sequences.

(3) Clinical and Other Features
A spreadsheet containing demographic, clinical, pathology, outcomes, genomic, and other information for the patients. The legend and column explanation are included in the spreadsheet (different tabs).

(4) Imaging features
A spreadsheet that contains 529 imaging features extracted from the images. These are the features that were used in the paper listed above (Saha et al., BJR 2018).

Acknowledgements

We would like to acknowledge the individuals and institutions that have provided data for this collection:

• Hospital/Institution Name city, state, country - Special thanks to First Last Names, degree PhD, MD, etc from the Department of xxxxxx, Additional Names from same location.

• Continue with any names from additional submitting sites if collection consists of more that one.