Datasets:

turab45
/

acdc_mnms2_processed

This dataset contains processed cardiac cine MRI data from the Automated Cardiac Diagnosis Challenge (ACDC) and the Multi-Centre, Multi-Vendor & Multi-Disease Cardiac Image Segmentation (M&Ms2) dataset. It is prepared for patient-level cardiac pathology classification with the CineMA preprocessing conventions.

The files are intended for research and education. This repository is a processed derivative of the source datasets; users must comply with the terms, access conditions, and citation requirements of the original ACDC and M&Ms2 datasets.

Dataset Details

Dataset Sources

ACDC: ACDC challenge
M&Ms: M&Ms challenge
Training code: Cardiac MRI classification repository

Uses

Direct Use

The processed files can be used for:

Training and evaluating supervised cardiac MRI classifiers.
Reproducing the ACDC and M&Ms2 experiments in the accompanying training code.
Comparing 2-D central-SAX and 3-D SAX model pipelines.
Developing data-loading, validation, and patient-level evaluation workflows.

The dataset is not intended to replace clinical assessment or to support diagnosis or treatment decisions.

Out-of-Scope Use

Do not use this dataset for:

Clinical diagnosis, triage, treatment planning, or other medical decisions.
Evaluating a model as clinically safe or ready for deployment without independent validation, regulatory review, and domain-expert oversight.
Re-identification, linkage with external personal records, or attempts to infer information about individual patients or data contributors.
Claims of performance on populations, scanners, hospitals, or acquisition protocols that are not represented in the source datasets.

Dataset Structure

The repository contains two processed subsets:

acdc/
  train_metadata.csv
  test_metadata.csv
  train/
  test/
mnms2/
  train_metadata.csv
  val_metadata.csv
  test_metadata.csv
  train/
  val/
  test/

The exact directory names and additional metadata files should be treated as part of the uploaded repository layout. Each patient directory contains processed cine MRI volumes. The classification loaders use SAX ED and ES images. Metadata includes patient identifiers, pathology labels, and the number of available slices where required by the preprocessing pipeline.

Labels and Splits

The expected patient-level labels and split sizes are:

Subset	Classes	Train	Validation	Test
ACDC	DCM, HCM, MINF, NOR, RV	90	10	50
M&Ms2	ARR, CIA, FALL, HCM, LV, NOR	160	30	110

The split counts refer to patients, not individual images or slices. The ACDC validation split is derived from the development/training metadata by the preprocessing and experiment pipeline. Images from the same patient must not be distributed across different splits.

For the 2-D central-SAX workflow, one deterministic central SAX slice is selected at end-diastole (ED) and one at end-systole (ES). These two phase images are stacked as a two-channel input. The 3-D workflow retains the corresponding volume data.

Dataset Creation

Curation Rationale

The dataset was processed to provide a reproducible input layout for cardiac MRI classification experiments. Processing keeps the patient-level organization and metadata needed for deterministic split validation and supports both 2-D and 3-D experiments.

Source Data

The source data are cardiac cine MRI examinations from the ACDC and M&Ms datasets. The source datasets contain data collected from clinical and research cohorts and include pathology categories defined by their respective challenge protocols.

Data Collection and Processing

The source datasets were processed using the CineMA data-preprocessing pipeline. The resulting files use NIfTI image volumes and CSV metadata. The downstream classification workflow performs intensity scaling and, during training, may apply contrast adjustment, Gaussian noise, affine augmentation, spatial cropping, and padding. These training-time augmentations are not part of the stored source files.

The processed dataset should be validated before use. In particular, check that metadata identifiers match patient directories, that ED and ES files are present, and that no patient occurs in more than one split.

Who are the source data producers?

The source images and labels were produced by the clinical and research groups described by the ACDC and M&Ms challenge organizers. This processed repository does not claim ownership of the original clinical data.

Annotations

The pathology labels are inherited from the source datasets and are used as classification targets. This repository does not add new clinical annotations.

Annotation process

See the original ACDC and M&Ms documentation for the source annotation protocols, label definitions, and quality-control procedures.

Who are the annotators?

The original source-dataset organizers and clinical experts are responsible for the source annotations. The identities and roles of individual annotators are not specified in this processed-data card.

Personal and Sensitive Information

Cardiac MRI is medical data and must be treated as sensitive. Patient identifiers in processed metadata are dataset identifiers, not permission to identify or link patients. Do not attempt re-identification or external linkage. Users should review the original dataset documentation and applicable institutional, ethical, and legal requirements before downloading or redistributing the files.

Bias, Risks, and Limitations

The dataset is limited to the populations, institutions, scanners, vendors, and acquisition protocols represented by ACDC and M&Ms.
Class frequencies and cohort composition may not represent clinical prevalence.
Performance can change substantially across hospitals, vendors, field strengths, protocols, demographics, and image-quality conditions.
A processed dataset can inherit errors, missing data, label noise, and selection bias from its source datasets.
Patient-level splits do not guarantee independence from every possible external dataset or acquisition site.
The labels are suitable for benchmarking the stated research tasks, not for establishing clinical severity or treatment recommendations.

Recommendations

Report the source subset, patient-level split, preprocessing version, model, augmentation settings, random seeds, and evaluation metrics. Use external and site-aware validation where possible, inspect errors by class and acquisition source, and involve qualified clinical experts before drawing clinical conclusions.

License and Attribution

This repository is a processed derivative of ACDC and M&Ms2. The appropriate use and redistribution terms are inherited from the original source datasets and may not be replaced by a blanket license for this processed copy. Before publishing models, derivatives, or analyses, review and follow the current terms supplied by the ACDC and M&Ms organizers.

Please cite the original ACDC and M&Ms publications or challenge pages, and cite the processing or training repository when using this processed release.