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Open Imaging Index
Mammography Breast

CBIS-DDSM

Curated Breast Imaging Subset of the Digital Database for Screening Mammography

Screening mammograms with mass and calcification outlines, BI-RADS descriptors and pathology labels, curated as a public benchmark for mammography CAD. 3,103 scanned-film mammograms of 1,566 women from the 1990s DDSM, converted to DICOM with a fixed train/test split.

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Overview

CBIS-DDSM is a cleaned-up and standardised selection from the Digital Database for Screening Mammography (DDSM), a collection of scanned film mammograms assembled in the 1990s. A Stanford group released it through The Cancer Imaging Archive in 2016-2017 so that mammography CAD methods could be compared on one public benchmark. It is used for mass and calcification classification, lesion detection and mass segmentation.

Composition

The collection covers 1,566 participants. The data descriptor reports 891 mass cases and 753 calcification cases; the public description tables list 3,568 abnormalities on 3,103 full mammograms in craniocaudal (CC) and mediolateral oblique (MLO) views. Every abnormality carries a pathology label (malignant, benign, or benign without callback), a BI-RADS assessment, a subtlety score, breast density and shape, margin, type or distribution descriptors. About a fifth of the cases form a test set, split separately for masses and calcifications and stratified by BI-RADS category. Besides the full images, the download contains ROI masks and square crops around each abnormality. In the DICOM headers every breast view has its own patient id, so TCIA's counters show 6,671 "patients".

Acquisition

DDSM mammograms came from Massachusetts General Hospital, Wake Forest University School of Medicine, Sacred Heart Hospital and Washington University in St Louis, digitised on several film scanners. The curators decompressed the obsolete lossless JPEG files, mapped pixel values to standardised optical density and stored the result as 16-bit DICOM.

Annotations

A trained mammographer reviewed questionable mass cases and removed 254 images in which the mass was not clearly visible. Mass outlines were refined with a level-set segmentation started from the original DDSM contours; calcification ROIs keep the original, coarse outlines.

Known limitations

  • Scanned film from decades ago; no digital mammography and no normal cases.
  • Calcification ROIs are imprecise.
  • Age and other demographics are not in the description tables, although DDSM recorded patient age.
  • Train and test are split per abnormality, so a few participants appear in both.

Cohort

Aggregate numbers from the sources below. Bars are relative to the 1,566 subjects.

Condition

Groups can overlap

  • Breast cancer 752 48%

From Mass and calcification case description CSVs, training and test (open download, CC BY 3.0), counted per participant id and per full-mammogram series

Split

Images
  • Training 2,458 79%
  • Test 645 21%

From Mass and calcification case description CSVs, training and test (open download, CC BY 3.0), counted per participant id and per full-mammogram series

Split by view

Images

Reported cross table. A dot marks a cell the source does not give.

Mediolateral obliqueCraniocaudal
Training1,2981,160
Test345300

From Mass and calcification case description CSVs, training and test (open download, CC BY 3.0), counted per participant id and per full-mammogram series

Anatomy

  • Breast 1,566 100%

From TCIA collection page CBIS-DDSM

View

  • Mediolateral oblique 1,473 94%
  • Craniocaudal 1,312 84%

From Mass and calcification case description CSVs, training and test (open download, CC BY 3.0), counted per participant id and per full-mammogram series

View by condition

Images

Reported cross table. A dot marks a cell the source does not give.

Breast cancer
Mediolateral oblique726
Craniocaudal649

From Mass and calcification case description CSVs, training and test (open download, CC BY 3.0), counted per participant id and per full-mammogram series

License and access

Our reading of the license, not legal advice. Before you use the data, read the original license and confirm that your use is allowed. We take no responsibility for how you use a dataset. Full disclaimer

Access
Open download

Download without an account

Access page

Creative Commons Attribution 3.0 Unported

Older version of CC BY. Use, share and adapt the data for any purpose, including commercial use, as long as you credit the creators.

TCIA lists the images and the four description CSV files under CC BY 3.0. Users must also agree to the TCIA Data Usage Policy, which says users must "Not use the requested datasets, either alone or in concert with any other information, to identify or contact individual participants" and must cite the dataset DOI (https://www.cancerimagingarchive.net/data-usage-policies-and-restrictions/).

Original license text Version read: 3.0 Checked 2026-10-07

What you can do

  • Yes
  • Yes
  • Yes
  • Yes
  • Yes

What you can share

  • Yes
  • Yes
  • Yes

What you must do

  • Yes
  • Share alike No
  • No
  • No
  • Manuscript review No
  • Release code No
  • Return results No
  • Delete after use No

Limits

  • No
  • Location limits No

Citation

Sawyer-Lee R, Gimenez F, Hoogi A, Rubin D. Curated Breast Imaging Subset of Digital Database for Screening Mammography (CBIS-DDSM) [Data set]. The Cancer Imaging Archive (2016). https://doi.org/10.7937/K9/TCIA.2016.7O02S9CY. Lee RS, et al. A curated mammography data set for use in computer-aided detection and diagnosis research. Sci Data 4, 170177 (2017).

Sources

Every number on this page comes from one of these documents. Each chart names the table or page it is taken from. The raw numbers are in stats.csv.