A European Multi-Center Breast Cancer MRI Dataset

TL;DR

This paper introduces a large, diverse, multi-center European breast MRI dataset to facilitate AI research, along with baseline benchmarks to support future developments in breast cancer detection.

Contribution

It provides the first publicly available, multi-center breast MRI dataset with heterogeneous data reflecting real-world variability, and establishes baseline transformer model performance.

Findings

Dataset includes 741 examinations from six institutions across Europe.

Baseline transformer model achieves initial performance benchmarks.

Dataset enables robust AI development for breast cancer detection.

Abstract

Early detection of breast cancer is critical for improving patient outcomes. While mammography remains the primary screening modality, magnetic resonance imaging (MRI) is increasingly recommended as a supplemental tool for women with dense breast tissue and those at elevated risk. However, the acquisition and interpretation of multiparametric breast MRI are time-consuming and require specialized expertise, limiting scalability in clinical practice. Artificial intelligence (AI) methods have shown promise in supporting breast MRI interpretation, but their development is hindered by the limited availability of large, diverse, and publicly accessible datasets. To address this gap, we present a publicly available, multi-center breast MRI dataset collected across six clinical institutions in five European countries. The dataset comprises 741 examinations from women undergoing screening or diagnostic breast MRI and includes malignant, benign, and non-lesion cases. Data were acquired using heterogeneous scanners, field strengths, and acquisition protocols, reflecting real-world clinical variability. In addition, we report baseline benchmark experiments using a transformer-based model to illustrate potential use cases of the dataset and to provide reference performance for future methodological comparisons.