README.md

---
license: cc-by-nc-sa-4.0
task_categories:
- image-segmentation
tags:
- medical
- ultrasound
- echocardiography
- 3d-echocardiography
- cardiac
- heart
- left-ventricle
- endocardium
- cetus
- miccai-2014
pretty_name: CETUS 2014 - Endocardial 3D Echocardiography LV Segmentation
size_categories:
- n<1K
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: case_id
    dtype: string
  - name: patient_id
    dtype: string
  - name: phase
    dtype: string
  - name: split
    dtype: string
  - name: image
    dtype: image
  - name: mask
    dtype: image
  - name: overlay
    dtype: image
  - name: overlay_long_axis
    dtype: image
  - name: shape_xyz
    dtype: string
  - name: n_slices
    dtype: int32
  - name: slice_index_short_axis
    dtype: int32
  - name: slice_index_long_axis
    dtype: int32
  - name: spacing_mm
    dtype: float32
  - name: fg_voxels
    dtype: int64
  - name: foreground_fraction
    dtype: float32
  - name: lv_volume_ml
    dtype: float32
  - name: ef_percent
    dtype: float32
  - name: intensity_max
    dtype: float32
  splits:
  - name: train
    num_bytes: 6727258
    num_examples: 90
  download_size: 6744464
  dataset_size: 6727258
---

# CETUS 2014 — Endocardial Three-dimensional Ultrasound Segmentation

The **MICCAI 2014 CETUS challenge**: segment the **left-ventricular endocardial
surface** in **3-D transthoracic echocardiography**, at end-diastole (ED) and
end-systole (ES).

This is 3-D echo, not 2-D. Where CAMUS gives you a 2-D apical plane, CETUS gives
a full pyramidal volume per cardiac phase — so the LV cavity is segmented as a
solid, and the ED/ES pair yields stroke volume and ejection fraction directly.

## What this mirror contains — read first

> **⚠️ ED and ES only. The full cardiac sequences are *not* in this release.**
> The 2014 challenge distributed complete cine loops as MHD/RAW through the
> now-decommissioned MIDAS server. The 2022 CREATIS Girder re-release mirrored
> here ships **exactly two frames per patient** — ED and ES — as NIfTI. There are
> no intermediate frames and no `ED_ES_time` metadata anywhere in the archive.
> Verified: all 45 patient folders contain exactly 4 files, zero exceptions.
> **Anything requiring the cardiac cycle cannot be reproduced from this release.**

> **⚠️ …but ground truth is now public for all 45 patients.** The challenge
> withheld the 30 test masks for its leaderboard. This release includes a
> `_gt.nii.gz` for **every** patient and **both** phases — 90 annotated volumes.
> So relative to 2014 this is *fewer frames but more labels*.

> **⚠️ There is no train/test split — and the original 15/30 assignment is not
> recoverable.** The archive is a flat list of 45 patient folders with no split
> file, no `Training/`/`Testing/` directories, and empty Girder metadata on every
> item. This mirror therefore ships **one `train` split containing all 45
> patients** and declares a split fallback, rather than inventing a boundary.
> Any published "CETUS test set" number refers to a partition this release does
> not identify.

> **⚠️ Beware third-party mirrors.** `zeahub/cetus-miccai-2014` reformats to HDF5
> and carves out a `test/` split (patients 39–45) that appears to drop ground
> truth — but **all 45 patients have GT here**, so that split is invented and its
> "test" set discards usable labels. Prefer this mirror or the CREATIS source.

## Dataset Details

| Field | Value |
|---|---|
| Modality | **3-D transthoracic echocardiography** (B-mode), volumetric |
| Body part | Heart — **left ventricle**, endocardial surface |
| Target | **LV endocardium (blood pool)** — single binary structure |
| Cases | **45 patients × 2 phases (ED, ES) = 90 annotated volumes** |
| Centres | Rennes University Hospital · University Hospitals Leuven · Erasmus MC Rotterdam |
| Vendors | GE Vivid E9 · Philips iE33 · Siemens SC2000 (per-patient vendor **not** published) |
| Volume shapes | **33 distinct**; 200–380 × 191–424 × 176–348 |
| Slices (z) | **176–348** per volume, median 231 |
| Spacing | **0.5763 mm isotropic** — see the units warning below |
| Format | `.nii.gz`; images **and** masks both `float32` |
| Mask values | **`{0.0, 255.0}`** — not `{0,1}`, not `uint8` |
| Split | **none upstream** — all 45 patients in `train` |
| License | **CC BY-NC-SA 4.0** — shipped inside the archive itself |
| Paper | Bernard et al., *IEEE TMI* **35**(4):967–977, 2016 · doi:10.1109/tmi.2015.2503890 |

## ⚠️ The header declares millimetres but stores metres

**The single easiest thing to get wrong with this dataset.**

Every one of the 90 volumes has:

```
xyzt_units = 2          # NIfTI code 2 == MILLIMETRES
pixdim     = (5.763e-4, 5.763e-4, 5.763e-4)
affine     = diag(-5.763e-4, -5.763e-4, +5.763e-4), zero translation
sform_code = 1, qform_code = 1
```

Taken literally that is **0.00058 mm** — 0.58 micrometres per voxel, i.e. a heart
the size of a bacterium. The values are **metres**; the true spacing is
**0.5763 mm isotropic**, uniform across every patient and every axis.

Confirmed physiologically rather than by assertion — computing LV volume from the
ground-truth voxel counts under the metres reading gives:

| | min | median | max |
|---|---|---|---|
| EDV (mL) | 79.9 | **139.5** | 407.9 |
| ESV (mL) | 36.0 | **87.8** | 352.7 |
| **EF (%)** | 13.5 | **38.2** | 56.7 |

Textbook values for a cardiac cohort (14/45 patients have EF < 30 %, 11/45 have
EDV > 200 mL — CETUS deliberately included impaired and dilated ventricles).
Under the literal-millimetres reading the same voxels give EDV ≈ 2.9 × 10⁻⁷ mL.

**Dice and other overlap metrics are unaffected.** Anything in physical units —
volume, ejection fraction, Hausdorff distance, mm-based resampling — is wrong by
10³ per axis unless you override the spacing. **The headers are deliberately NOT
patched here** so this mirror stays byte-identical to the official release; the
corrected spacing is recorded per case in `train.jsonl` as `spacing_mm`.

## ⚠️ Masks are float32 `{0.0, 255.0}`

Both the image *and* the mask are stored `float32`, and the mask's header is
**byte-identical to its image's header** in all 90 pairs. Foreground is `255.0`,
not `1`.

**Binarize on the raw values (`arr > 0`).** Measured over all 90 masks: exactly
two unique values, no intermediate/anti-aliased voxels, no empty masks, and the
image/mask grids always agree. A `{0,255}` binary mask survives a min–max→`>0.5`
recipe, but reading the raw values is the honest operation and is what the
official notebook does.

All 90 **images** are likewise integral and within 0–255 despite the float32
container, so they are losslessly `uint8`-representable — the float32 storage
costs 4× for nothing. Files are mirrored as-is regardless.

## Ground truth

**One reference mask per volume — there is no tier or rater to choose.** The
challenge's evaluation protocol involved three expert observers to establish
inter-observer variability, but the distributed `_gt.nii.gz` is a single
consensus reference, and it is the only annotation released.

Measured over all 90 masks:

| | min | median | max |
|---|---|---|---|
| Foreground fraction of volume | 1.20 % | **3.35 %** | 6.84 % |

- **Zero empty masks** — every one of the 90 volumes has annotated foreground.
- **ED cavity > ES cavity in 45/45 patients**, as physiology requires. This is a
  free correctness check on the phase labelling, and it passes without exception.

## Choosing a slicing axis — axis 2 (z)

For 2-D slice-wise use, **axis 2 is both the anatomically correct stack and the
empirically best choice.** It is the beam/depth axis, running apex → base, so
slicing it yields the conventional **short-axis** cross-sections; axes 0 and 1
yield long-axis (apical) views.

Measured over all 90 masks:

| Axis | View | Slices containing foreground (median) | Leading background slices (median) |
|---|---|---|---|
| 0 | long-axis | 31.6 % | 102 |
| 1 | long-axis | 32.7 % | 88 |
| **2 (z)** | **short-axis** | **64.4 %** | **41** |

Axis 2 roughly doubles the fraction of useful slices and more than halves the
leading empty run — which matters for any pipeline that samples slices at random
and gives up after a bounded number of attempts.

Note the organizers' own `script_cetus.ipynb` (carried over here) visualises
along a *long-axis* plane. That is a display choice, not a processing convention.

## Structure

```
train/images/patient01_ED.nii.gz    #  90 B-mode volumes (45 patients x ED/ES)
train/masks/patient01_ED.nii.gz     #  90 masks, same grid, values {0., 255.}
train.jsonl                         # per-case metadata (90 rows)
manifest.csv                        # sha256 + bytes + shape for all 180 originals
script_cetus.ipynb                  # organizers' official reader, verbatim
LICENSE_TERMS.md                    # from the archive, verbatim
MANDATORY_CITATION.md               # from the archive, verbatim
README.md
LICENSE.txt
```

Case IDs are `patient01_ED` … `patient45_ES`; patient folders upstream are
lowercase, zero-padded 2-digit (`patient01`, not `Patient1` — that was the 2014
MHD release).

> **Group on `patient_id`, not `case_id`.** Each patient contributes two rows
> (ED and ES) of the *same* heart on the *same* grid. Splitting them across a
> train/test boundary leaks.

`train.jsonl` columns:

| Column | Meaning |
|---|---|
| `case_id` | `"patient01_ED"` — unique per row |
| `patient_id` | `"patient01"` — **the grouping key**; 2 rows share it |
| `phase` | `"ED"` or `"ES"` |
| `image`, `mask` | repo-relative paths |
| `split` | always `"train"` (no upstream split exists) |
| `shape_xyz`, `n_slices` | geometry; `n_slices` is the axis-2 extent |
| `spacing_mm` | **`[0.5763, 0.5763, 0.5763]` — corrected**, use this |
| `pixdim_raw`, `xyzt_units_code` | what the header literally says (the defect) |
| `axcodes`, `sform_code`, `qform_code` | header provenance |
| `image_dtype`, `mask_dtype` | both `float32` |
| `intensity_min`, `intensity_max` | per-volume; 88/90 span 0–255 |
| `image_fits_uint8` | `true` for all 90 |
| `mask_values` | `[0.0, 255.0]` for all 90 |
| `fg_voxels`, `n_voxels`, `foreground_fraction` | cavity size |
| `lv_volume_ml` | `fg_voxels x 0.5763^3 / 1000` — corrected spacing |
| `ef_percent` | patient-level EF from this patient's ED/ES pair |
| `fg_slice_fraction`, `leading_bg_slices` | per-axis (`"0"`,`"1"`,`"2"`) coverage |
| `image_sha256`, `mask_sha256`, `image_bytes`, `mask_bytes` | fidelity to source |

## Overlap and contamination

- **CAMUS — believed disjoint, but not provably so.** CAMUS is single-centre
  (Saint-Étienne) 2-D echo; CETUS is three-centre (Rennes / Leuven / Rotterdam)
  3-D echo. Different modality, cohorts and scanners. **No author asserts
  disjointness**, and both releases use positional anonymous IDs (`patient01…`),
  so overlap is **unverifiable by ID even in principle**. What the two genuinely
  share is authors (Bernard, D'hooge, Pedrosa), not patients. Note the ID schemes
  collide — namespace by dataset key.
- **⚠️ CETUS2014 appears in the IMed-361M / IMIS-Net training corpus** (arXiv
  2411.12814, Table 4, cited to the CREATIS challenge URL, 90/10 split).
  Benchmarking IMIS-Net on CETUS is **contaminated**.
- **Clean with respect to MedSAM, SAMUS/US30K, UltraSam/US-43d, MedSAM2,
  SAM-Med2D, SAM-Med3D and BiomedParse** — those corpora absorbed *CAMUS*, not
  CETUS. "CETUS" appears zero times in MedSAM's supplement.
- No overlap with EchoNet-Dynamic (Stanford), MITEA, or the Medical Segmentation
  Decathlon (which contains no echocardiography at all).

## Known per-case notes

- `patient29` is the only intensity outlier: max **168** (ED) / **190** (ES)
  rather than 255 — a dimmer acquisition, not a truncated file.
- Volume shape is unique per patient (33 distinct shapes over 45 patients); ED
  and ES always share their patient's shape.

## Source & Citation

- Official: CREATIS Human Heart Project Girder, collection
  `62eb991b73e9f0048c3a6c45` — served anonymously, no account required.
  `https://humanheart-project.creatis.insa-lyon.fr/database/`
- The same server hosts the official ACDC, CAMUS and TED releases.

```bibtex
@article{bernard2016cetus,
  author  = {Bernard, Olivier and Bosch, Johan G. and Heyde, Brecht and
             Alessandrini, Martino and Barbosa, Daniel and Camarasu-Pop, Sorina
             and Cervenansky, Frederic and Valette, Sebastien and Mirea, Oana
             and Bernier, Michel and Jodoin, Pierre-Marc and Domingos, Joao S.
             and Stebbing, Richard V. and Keraudren, Kevin and Oktay, Ozan and
             Caballero, Jose and Shi, Wenzhe and Rueckert, Daniel and
             Milletari, Fausto and Ahmadi, Seyed-Ahmad and Smistad, Erik and
             Lindseth, Frank and van Stralen, Marijn and Wang, Chen and
             Smedby, Orjan and Donal, Erwan and Monaghan, Mark and
             Papachristidis, Alexandros and Geleijnse, Marcel L. and
             Galli, Elena and D'hooge, Jan},
  title   = {Standardized Evaluation System for Left Ventricular Segmentation
             Algorithms in {3D} Echocardiography},
  journal = {IEEE Transactions on Medical Imaging},
  volume  = {35},
  number  = {4},
  pages   = {967--977},
  year    = {2016},
  doi     = {10.1109/TMI.2015.2503890}
}
```