# fastMRI Breast: A publicly available radial k-space dataset of breast dynamic contrast-enhanced MRI

arXiv: https://arxiv.org/abs/2406.05270 · HTML: https://mlsanity.com/paper/2406.05270/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Jun 2024.

## Built on by (most cited first, 7 of 7)

- [A European Multi-Center Breast Cancer MRI Dataset](https://mlsanity.com/paper/2506.00474/) (2025)
- [PhaseGen: A Diffusion-Based Approach for Complex-Valued MRI Data Generation](https://mlsanity.com/paper/2504.07560/) (2025)
- [Mind the Detail: Uncovering Clinically Relevant Image Details in Accelerated MRI with Semantically Diverse Reconstructions](https://mlsanity.com/paper/2507.00670/) (2025)
- [MosaicMRI: A Diverse Dataset and Benchmark for Raw Musculoskeletal MRI](https://mlsanity.com/paper/2604.11762/) (2026)
- [Robustness of breast lesion segmentation under MRI undersampling improves with k-space-aware deep learning](https://mlsanity.com/paper/2605.22327/) (2026)
- [Cross-Dataset Generalization in Breast MRI Tumor Classification via Class-Wise Dataset Mixing](https://mlsanity.com/paper/2607.18678/) (2026)
- [Anguinus Sculpturae: Compositional Synthesis of Peak-Enhancement Breast DCE-MRI Scans](https://mlsanity.com/paper/2609.33611/) (2026)

## Abstract (arXiv)

This data curation work introduces the first large-scale dataset of radial k-space and DICOM data for breast DCE-MRI acquired in diagnostic breast MRI exams. Our dataset includes case-level labels indicating patient age, menopause status, lesion status (negative, benign, and malignant), and lesion type for each case. The public availability of this dataset and accompanying reconstruction code will support research and development of fast and quantitative breast image reconstruction and machine learning methods.