AI for Impact on Breast Cancer
Free Annotated Mammogram Dataset to Advance AI Research in Breast Cancer Detection
Collaboration for Women’s Health
Request Access
This dataset provides access to a curated collection of annotated Digital Breast Tomosynthesis (DBT) studies intended to support academic and translational research in breast cancer detection and imaging AI.
Dataset Summary
• 558 female patients
• Digital Breast Tomosynthesis (3D Mammography)
• 271 malignant (48.5%) / 287 benign (51.5%) cases
• Average size: 1.34 cm
• Approximately 85% of lesions <2 cm
• Expert segmentation annotations
• DICOM, NRRD, and structured JSON outputs
• Fully de-identified in compliance with HIPAA and GDPR
Intended Research Applications
• Supervised learning for lesion detection and classification
• Segmentation model development
• Early-stage cancer detection research
• Model benchmarking and validation studies
• Comparative studies in DBT imaging
Data Access
The dataset is available at no cost to registered researchers for research use.To request access, please complete the registration form including institutional affiliation and intended research purpose.
Citation & Acknowledgment
Users of this dataset are requested to acknowledge the collaboration between iMerit, Segmed, and Advocate Health in resulting publications.
For more information, you can refer to the Release Announcement or contact support@segmed.ai
Dataset Summary
• 558 female patients
• Digital Breast Tomosynthesis (3D Mammography)
• 271 malignant (48.5%) / 287 benign (51.5%) cases
• Average size: 1.34 cm
• Approximately 85% of lesions <2 cm
• Expert segmentation annotations
• DICOM, NRRD, and structured JSON outputs
• Fully de-identified in compliance with HIPAA and GDPR
Intended Research Applications
• Supervised learning for lesion detection and classification
• Segmentation model development
• Early-stage cancer detection research
• Model benchmarking and validation studies
• Comparative studies in DBT imaging
Data Access
The dataset is available at no cost to registered researchers for research use.To request access, please complete the registration form including institutional affiliation and intended research purpose.
Citation & Acknowledgment
Users of this dataset are requested to acknowledge the collaboration between iMerit, Segmed, and Advocate Health in resulting publications.
For more information, you can refer to the Release Announcement or contact support@segmed.ai
