---
license: cc-by-nc-sa-4.0
pretty_name: "ISLES'24 (Ischemic Stroke Lesion Segmentation Challenge 2024)"
task_categories:
- image-segmentation
tags:
- medical
- medical-imaging
- stroke
- brain
- ct
- cta
- ct-perfusion
- mri
- dwi
- segmentation
- isles
size_categories:
- n<1K
---

# ISLES'24 - Ischemic Stroke Lesion Segmentation Challenge 2024

A real-world, **longitudinal, multimodal** acute-stroke dataset: acute admission
CT (NCCT, CTA, 4D CT-perfusion + derived perfusion maps), follow-up MRI
(DWI/ADC), and clinical tabular data, with the **final infarct lesion** as the
segmentation target.

> **This repository mirrors the public TRAINING set only (149 cases).** The
> 98-case ISLES'24 test set is withheld by the organizers for challenge scoring
> on Grand Challenge and is **not** part of any public release.

## Provenance

- **Official source:** Zenodo record **16748089** - *"ISLES'24 - A Real-World
  Longitudinal Multimodal Stroke Dataset"*, `train.7z`, CC BY-NC-SA 4.0
  (author-provided; not a third-party re-host).
- **Challenge:** https://isles-24.grand-challenge.org/
- **Code / data-loading reference:** https://github.com/ezequieldlrosa/isles24
- This mirror is an **unmodified raw copy** of the released volumes (no
  resampling, no intensity changes), with two documented exceptions below.

## Counts & faithfulness notes

- **149 training cases** (`sub-stroke0001` ... `sub-stroke0189`, non-contiguous):
  University Hospital Munich (TUM) + University Hospital Zurich.
- The companion paper reports **N=150** for training; the public Zenodo release
  ships **149** (one case excluded upstream). This mirror = the 149 released.
- **Dropped duplicate:** the upstream release contains one stray uncompressed
  file `sub-stroke0142_ses-02_lesion-msk.nii` (a native-space leftover). Subject
  0142 also has the standard co-registered `*_space-ncct_lesion-msk.nii.gz` like
  every other case, so this mirror keeps the standard GT and omits the stray.

## Structure (BIDS)

```
<sub>/                      sub-stroke0001 ... sub-stroke0189  (149)
  ses-01  = acute admission CT
  ses-02  = follow-up MRI (2-9 days later)

raw_data/<sub>/ses-01/                     # native acquisition space
  *_ncct.nii.gz   *_cta.nii.gz   *_ctp.nii.gz (4D, 55 timepoints)
  perfusion-maps/ *_{cbf,cbv,mtt,tmax}.nii.gz

derivatives/<sub>/                         # ALL co-registered to NCCT (space-ncct)
  ses-01/ *_space-ncct_cta.nii.gz  *_space-ncct_ctp.nii.gz (4D)
          *_space-ncct_lvo-msk.nii.gz      # large-vessel occlusion (CTA), binary
          *_space-ncct_cow-msk.nii.gz      # Circle-of-Willis anatomy (CTA), multi-class
          perfusion-maps/ *_space-ncct_{cbf,cbv,mtt,tmax}.nii.gz
  ses-02/ *_space-ncct_dwi.nii.gz  *_space-ncct_adc.nii.gz
          *_space-ncct_lesion-msk.nii.gz   # <-- GROUND TRUTH (final infarct), binary

phenotype/<sub>/ses-*/ *_demographic_baseline.csv  *_outcome.csv
```

**Co-registration:** within each subject, the raw NCCT and every
`derivatives/*space-ncct*` volume (CTA, perfusion maps, DWI/ADC, all masks)
share an identical voxel grid (shape, spacing, affine). The raw NCCT itself is
the reference space (hence there is no `space-ncct_ncct`). So a fully aligned
input+label stack = raw `ncct` + the `derivatives` `space-ncct` modalities +
`space-ncct_lesion-msk`.

## Ground truth

| Mask | Space | Type | Role |
|------|-------|------|------|
| `space-ncct_lesion-msk` (ses-02) | NCCT | binary {0,1} | **Gold standard** - final infarct lesion, the challenge target |
| `space-ncct_lvo-msk` (ses-01) | NCCT | binary {0,1} | Auxiliary - large-vessel occlusion (on CTA) |
| `space-ncct_cow-msk` (ses-01) | NCCT | multi-class | Auxiliary - Circle-of-Willis anatomy (on CTA) |

The **gold-standard lesion mask** is derived from the follow-up **DWI**: masks
were auto-generated by **DeepISLES** (the productized ISLES'22 winning ensemble)
and then **quality-controlled / manually corrected and verified by two
neuroradiologists** (>10 years' experience). The neuroradiologist-verified DWI
lesion is the reference standard; it is provided co-registered into NCCT space.

## Cross-dataset overlap (leakage note)

- **No patient reuse** from **ISLES'22** (a different, MRI-only DWI cohort).
  ISLES'24 is a new acute-stroke CT cohort. Modality and patients differ.
- There is **center-level** overlap (Munich contributes to both editions) and a
  **methodological** dependency (ISLES'24 GT masks are produced by DeepISLES,
  which was trained on ISLES'22) - but neither is shared imaging.
- No shared TCIA / BraTS / Medical Segmentation Decathlon lineage. Identifiers
  are challenge-internal BIDS `sub-stroke####` IDs only.

## License

**CC BY-NC-SA 4.0** (per the Zenodo deposit). Non-commercial, share-alike,
attribution required.

## Citation

```bibtex
@article{delarosa2024isles24,
  title   = {ISLES'24: Final Infarct Prediction with Multimodal Imaging and Clinical Data. Where Do We Stand?},
  author  = {de la Rosa, Ezequiel and Su, Ruisheng and Reyes, Mauricio and Riedel, Eda Otman and Baazaoui, Hakim and Wiest, Roland and Kofler, Florian and Kirschke, Jan S. and Wiestler, Benedikt and Menze, Bjoern},
  journal = {arXiv preprint arXiv:2408.10966},
  year    = {2024}
}
```

Data: Zenodo record 16748089 (de la Rosa et al., 2025). Please also credit the
ISLES'24 challenge organizers and the contributing hospitals (TUM Munich, USZ
Zurich).