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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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BreastDCEDL_ISPY2 - DCE MRI dataset 982 cases

Deep Learning ready DCE MRI 3D dataset 982 cases
Authors: Fridman, Naomi;

BreastDCEDL_ISPY2 - DCE MRI dataset 982 cases

Abstract

BreastDCEDL_ISPY2 Dataset (n=982) The BreastDCEDL_ISPY2 dataset is a curated subset of the I-SPY2 trial, comprising 982 breast cancer cases with pre-treatment DCE-MRI scans. It includes: DCE-MRI sequences (3–12 time points per scan, typically 7) Derived maps and full 3D tumor segmentations Clinical annotations: pathological complete response (pCR), hormone receptor (HR) status, HER2 status, MammaPrint risk level, and age at screening Demo: https://github.com/naomifridman/BreastDCEDL/blob/main/ISPY2/BrestDCEDL_ISPY2_demo.ipynb Citation @article{fridman2026breastdcedl, author = {Fridman, N. and Solway, B. and Fridman, T. and others}, title = {{BreastDCEDL}: A standardized deep learning-ready breast {DCE-MRI} dataset of 2,070 patients}, journal = {Scientific Data}, year = {2026}, doi = {10.1038/s41597-026-06589-6}, url = {https://doi.org/10.1038/s41597-026-06589-6}} Dataset Specifications Total Patients: 982 Total Size: ~54 GB Image Format: NIfTI (.nii.gz) Clinical Centers: 22+ institutions File Organization BreastDCEDL_ISPY2/ ├── BreastDCEDL_ISPY2_metadata.csv # Clinical and demographic data ├── dce/ # DCE-MRI sequences │ ├── ACRIN-6698-102212/ │ │ ├── ACRIN-6698-102212_spy2_vis1_dce_aqc_0.nii.gz # Pre-contrast │ │ ├── ACRIN-6698-102212_spy2_vis1_dce_aqc_1.nii.gz # Post-contrast 1 │ │ ├── ACRIN-6698-102212_spy2_vis1_dce_aqc_2.nii.gz # Post-contrast 2 │ │ ├── ACRIN-6698-102212_spy2_vis1_dce_aqc_3.nii.gz # Post-contrast 3 │ │ ├── ACRIN-6698-102212_spy2_vis1_dce_aqc_4.nii.gz # Post-contrast 4 │ │ ├── ACRIN-6698-102212_spy2_vis1_dce_aqc_5.nii.gz # Post-contrast 5 │ │ └── ACRIN-6698-102212_spy2_vis1_dce_aqc_6.nii.gz # Post-contrast 6 │ ├── ACRIN-6698-103939/ │ │ └── ... (3-12 DCE time points, typically 7) │ └── ... (982 patient directories total) └── masks/ # Tumor segmentations ├── ACRIN-6698-102212_spy2_vis1_mask.nii.gz ├── ACRIN-6698-103939_spy2_vis1_mask.nii.gz └── ... (982 binary mask files) Data Components Example of all acquisitions for random 7 patients, whith all the acquisitions. Resources Demo: https://github.com/naomifridman/BreastDCEDL/blob/main/ISPY2/BrestDCEDL_ISPY2_zenodo_demo.ipynb Full Methodology: Fridman et al., 2025 - arXiv:2506.12190 https://arxiv.org/abs/2506.12190 Citation @article{fridman2025breastdcedl, title={BreastDCEDL: A Comprehensive Breast Cancer DCE-MRI Dataset and Transformer Implementation for Treatment Response Prediction}, author={Fridman, Naomi and Solway, Bubby and Fridman, Tomer and Barnea, Itamar and Goldstein, Anat}, journal={arXiv preprint arXiv:2506.12190}, year={2025}, doi={10.48550/arXiv.2506.12190} }

Keywords

pCR prediction, breast cancer, ER, HER2, Rh-Hr Blood-Group System/chemistry, HR, medical imaging, deep learning, tumor segmentation, dynamic contrast-enhanced MRI, PR, breast MRI

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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Cancer Research