---
license: cc-by-4.0
pretty_name: ISLES 2016 (Ischemic Stroke Lesion Segmentation Challenge 2016)
task_categories:
- image-segmentation
tags:
- medical
- medical-imaging
- stroke
- brain
- mri
- perfusion
- perfusion-mri
- dwi
- lesion-outcome-prediction
- segmentation
- isles
size_categories:
- n<1K
dataset_info:
  features:
  - name: case_id
    dtype: string
  - name: space
    dtype: string
  - name: shape
    dtype: string
  - name: n_slices
    dtype: int32
  - name: display_slice
    dtype: int32
  - name: lesion_voxels
    dtype: int64
  - name: adc
    dtype: image
  - name: tmax
    dtype: image
  - name: mtt
    dtype: image
  - name: rcbf
    dtype: image
  - name: rcbv
    dtype: image
  - name: ttp
    dtype: image
  - name: gt_overlay_adc
    dtype: image
  - name: gt_overlay_tmax
    dtype: image
  splits:
  - name: train
    num_bytes: 4406129
    num_examples: 30
  download_size: 4412373
  dataset_size: 4406129
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# ISLES 2016 - Ischemic Stroke Lesion Segmentation Challenge 2016

Brain-MRI ischemic-stroke dataset from the MICCAI 2016 ISLES challenge. This is a
**lesion-OUTCOME-PREDICTION** task, not conventional visible-lesion segmentation:
the inputs are **acute** perfusion-derived MR maps, while the ground-truth mask is
the **final infarct** traced on a **~90-day follow-up** scan and mapped back into
the acute imaging space.

> **Read before benchmarking.** A model is asked to *predict future tissue fate*
> from acute perfusion imaging - the target lesion is generally **not directly
> visible** in any single input map. Scores are not comparable to
> visible-pathology segmentation sets (e.g. ISLES'22 DWI infarct segmentation).

> **This repository mirrors the public TRAINING set only (30 cases).** The 19
> ISLES 2016 test cases are withheld by the organizers (no public GT) and are
> **not** part of this release.

## Provenance

- **Official source:** Zenodo record **17736412** - *"ISLES (Ischemic Stroke
  Lesion Segmentation/Prediction) Challenge Datasets (2015, 2016, 2017, 2018)"*,
  files `ISLES2016_Training_{Native,CoRegistered}.zip`. Deposited by the original
  ISLES organizers (Reyes, de la Rosa, Menze), 2025 - author-provided, **not** a
  third-party re-host.
- The original host **SMIR / virtualskeleton.ch is decommissioned**; the Zenodo
  archive is the only live source.
- This mirror is an **unmodified raw copy** of the released volumes (no
  resampling, no intensity changes, original folder layout and case IDs).

## Counts & faithfulness notes

- **30 training cases**, in both spaces. Folder IDs are the original
  `training_1 ... training_35` numbering with **5 cases withdrawn** in the public
  V3 release - **missing IDs: 3, 17, 25, 29, 34**. The original IDs are preserved
  (they cross-reference the challenge paper and the ISLES 2017 superset).
- The peer-reviewed challenge paper (Winzeck et al. 2018) reports **35** training
  / 19 test; the public `TrainingV3` release ships **30** training. This mirror =
  the 30 publicly released training cases.
- Each case keeps the per-folder original license notice (`License_ODC_ODBL.txt`)
  and, for 4D PWI, a timing `.csv` - both retained as-is.

## Structure

```
TrainingV3_Native/        training_<n>/   # each modality in its native acquisition grid
TrainingV3_CoRegistered/  training_<n>/   # all modalities resampled to a common grid

training_<n>/VSD.Brain.XX.O.MR_<MOD>.<id>/VSD.Brain.XX.O.MR_<MOD>.<id>.nii
training_<n>/VSD.Brain.XX.O.OT.<id>/VSD.Brain.XX.O.OT.<id>.nii   # <-- GROUND TRUTH
```

The numeric `<id>` in each VSD folder name **differs between the two spaces** and
between modalities, so load by the modality token (`MR_ADC`, `OT`, ...), not by ID.

| Folder token | Modality | Dim | Notes |
|---|---|---|---|
| `MR_4DPWI` | Raw perfusion-weighted imaging | 4D | Source time-series; large (~112-199 MB/case) |
| `MR_ADC`  | Apparent diffusion coefficient | 3D | Diffusion (lesion-core proxy) |
| `MR_MTT`  | Mean transit time | 3D | Perfusion map |
| `MR_rCBF` | Relative cerebral blood flow | 3D | Perfusion map |
| `MR_rCBV` | Relative cerebral blood volume | 3D | Perfusion map |
| `MR_Tmax` | Time-to-maximum | 3D | Perfusion map (>6 s ~ hypoperfusion) |
| `MR_TTP`  | Time-to-peak | 3D | Perfusion map |
| `OT`      | **Ground-truth lesion** | 3D | **Binary final-infarct mask** |

**Native vs CoRegistered.** For segmentation use the **CoRegistered** space:
within each subject every map and the `OT` mask share one voxel grid, so inputs
and label align directly. The Native space preserves each modality's own
acquisition geometry.

## Ground truth

Single tier: the `OT` mask - the **final infarct lesion**, manually delineated by
neuroradiologists on the **~90-day follow-up** imaging and provided in the acute
imaging space. Binary {0, 1}. There are no multi-rater or partial-annotation
tiers to choose between.

## Cross-dataset overlap (leakage note)

- **ISLES 2017 is a SUPERSET.** Per Winzeck et al. 2018 the 2017 training cohort
  (43 cases) extends the 2016 cohort (35) with 8 new cases; these 30 publicly
  released 2016 cases are therefore a **subset of ISLES 2017's training data**.
  Concretely, in the sibling mirror **`Angelou0516/isles2017`** the 30
  **VSD-prefixed** cases carry the *identical* `training_<n>` numbering and the
  same withdrawn IDs {3, 17, 25, 29, 34} (and the same 5D 4D-PWI layout) as this
  set - i.e. they **are** these cases - while the 13 **SMIR-prefixed** cases are
  the 2017-only additions. **Never benchmark ISLES 2016 and ISLES 2017 as
  independent sets**; de-duplicate by matching `training_<n>`.
- **vs ISLES'22** (MRI DWI infarct *segmentation*): different task, different
  cohort - **no known patient reuse**.
- **vs ISLES'24** (CT-centric multimodal stroke): different modality and patients
  - **no overlap**.
- No BraTS / Medical Segmentation Decathlon / TCIA lineage.

## License

Re-released on Zenodo under **CC BY 4.0** (record 17736412). The original
SMIR-era per-file notices embedded in each folder are **ODC-ODbL**
(`License_ODC_ODBL.txt`), retained unmodified. Both permit redistribution with
attribution.

## Citation

```bibtex
@article{winzeck2018isles,
  title   = {ISLES 2016 and 2017-Benchmarking Ischemic Stroke Lesion Outcome Prediction Based on Multispectral MRI},
  author  = {Winzeck, Stefan and Hakim, Arsany and McKinley, Richard and Reyes, Mauricio and others},
  journal = {Frontiers in Neurology},
  volume  = {9},
  pages   = {679},
  year    = {2018},
  doi     = {10.3389/fneur.2018.00679}
}
```

Data: Zenodo record 17736412 (Reyes, de la Rosa, Menze, 2025). Please credit the
ISLES 2016 challenge organizers.