We are thrilled to announce a major milestone for BCN-AIM! Our lab member, Lidia Garrucho Moras, has published in Scientific Data about the MAMA-MIA Breast Cancer DCE-MRI dataset, now publicly available. This dataset marks a significant step forward for AI research in breast cancer imaging.

Addressing a Critical Gap in Breast Cancer AI
Developing reliable AI models for breast cancer MRI has been challenging due to the scarcity of large, expert-annotated datasets. MAMA-MIA changes that by providing the largest publicly available breast DCE-MRI dataset with expert-validated 3D tumor segmentations. This enables groundbreaking AI research for cancer diagnosis and treatment.

Key Features of MAMA-MIA

1. Automatic Tumor Segmentation

• Includes 1,506 expert-validated 3D segmentations
• Supports the development of generalizable, robust AI models
• Pre-trained nnU-Net weights available as a baseline

2. Treatment Response & Survival Prediction

• Provides clinical and treatment outcomes for 1,506 cases
• Enables AI models to predict response to neoadjuvant chemotherapy (NAC)

3. Segmentation Quality Control

• Facilitates research into AI-driven quality control for clinical applications

4. Image Synthesis & Standardization

• Diverse dataset from multiple scanners, protocols, and institutions
• Supports image standardization, domain adaptation, and bias mitigation

5. Fine-Tuning Foundational AI Models

• Enables the adaptation of multimodal foundation models for breast MRI tasks

Usefull links:
📖 Read the full paper: here.

⬇️ Download the dataset: here.

We are excited to see how the research community will leverage MAMA-MIA to advance AI in breast cancer imaging!