YongchengYAO/MAMA-MIA-Lite

About

This is a preprocessed redistribution of MAMA-MIA (Synapse syn60868042), which is released under the CC BY-NC 4.0 license.

Dataset summary: 1506 breast DCE-MRI scans with expert primary-tumour segmentation masks.

Contents of this repository:

• Images/ — 1506 files
• Masks/ — 1506 files

📝 Landmark annotations, visualization figures and the benchmark plan files live in 🔥MedVision🔥, where you can load the complete images and annotations from dataset configs.

Relation to the source dataset

In the source	1506 cases, each with a pre-contrast volume plus several post-contrast DCE phases
Excluded here	every DCE phase except the annotated first post-contrast (_0001)
In this repo	1506 Images + 1506 Masks

All 1506 cases are included, but only one DCE phase per case. Each case ships a pre-contrast volume (_0000) plus several post-contrast phases (_0001, _0002, ...); the expert tumour mask is drawn on the first post-contrast phase, so only _0001 is redistributed. The other phases are not annotated and would not be measurable.

Why -Lite? The suffix marks this as a derived redistribution rather than a copy of the source. These are preprocessed volumes — every case has been format-converted, geometry-normalised and reoriented to RAS+ — and for some sources cases or modalities are excluded as well (see the table above). Use it to reproduce MedVision, not as a substitute for the original release. See Preprocessing below for exactly what was changed.

Preprocessing

• The first post-contrast volume (_0001) is used as the image, matching the phase the expert mask was drawn on (convention confirmed against the official MAMA-MIA/src/preprocessing.py::read_mri_phase_from_patient_id).

• Images and masks standardized to RAS+ orientation; masks cast to uint16.

• Image/mask pairs whose headers disagree on grid geometry are excluded.

Segmentation Labels

labels_map = {
    "1": "breast tumor"
}

Landmarks

landmarks_map = {
    "P1": "most right/anterior/superior endpoint of the major axis",
    "P2": "most left/superior/inferior endpoint of the major axis",
    "P3": "most right/anterior/superior endpoint of the minor axis",
    "P4": "most left/superior/inferior endpoint of the minor axis"
}

News

• [25 Jul, 2026] Initial release. This dataset is integrated into 🔥MedVision🔥, where you can use these config names to load data in python:

  • MAMA-MIA_BoxSize_Task01_Axial_Test
  • MAMA-MIA_BoxSize_Task01_Axial_Train
  • MAMA-MIA_BoxSize_Task01_Coronal_Test
  • MAMA-MIA_BoxSize_Task01_Coronal_Train
  • MAMA-MIA_BoxSize_Task01_Sagittal_Test
  • MAMA-MIA_BoxSize_Task01_Sagittal_Train
  • MAMA-MIA_MaskSize_Task01_Axial_Test
  • MAMA-MIA_MaskSize_Task01_Axial_Train
  • MAMA-MIA_MaskSize_Task01_Coronal_Test
  • MAMA-MIA_MaskSize_Task01_Coronal_Train
  • MAMA-MIA_MaskSize_Task01_Sagittal_Test
  • MAMA-MIA_MaskSize_Task01_Sagittal_Train
  • MAMA-MIA_TumorLesionSize_Task01_Axial_Test
  • MAMA-MIA_TumorLesionSize_Task01_Axial_Train

Data Usage Agreement

By using the dataset, you agree to the terms as follow.

• You must comply with the original CC BY-NC 4.0 license terms of the source dataset.
• You are recommended to refer to the source of this dataset in any publication: https://huggingface.co/datasets/YongchengYAO/MAMA-MIA-Lite
• You must cite the original publication(s):
  • https://doi.org/10.1038/s41597-025-04707-4
  • https://arxiv.org/abs/2603.01250

Official Release

For more information, please go to the official site: https://github.com/LidiaGarrucho/MAMA-MIA

Download from Huggingface

# python
from huggingface_hub import snapshot_download
snapshot_download(repo_id="YongchengYAO/MAMA-MIA-Lite", repo_type='dataset', local_dir="/your/local/folder")