Datasets:
case_id stringlengths 6 6 | split stringclasses 1
value | num_slices int32 15 54 | height int32 256 512 | width int32 256 512 | image imagewidth (px) 256 512 | mask imagewidth (px) 256 512 | overlay imagewidth (px) 256 512 |
|---|---|---|---|---|---|---|---|
Case00 | train | 47 | 512 | 512 | |||
Case01 | train | 29 | 512 | 512 | |||
Case02 | train | 54 | 512 | 512 | |||
Case03 | train | 42 | 512 | 512 | |||
Case04 | train | 46 | 512 | 512 | |||
Case05 | train | 42 | 512 | 512 | |||
Case06 | train | 39 | 512 | 512 | |||
Case07 | train | 34 | 512 | 512 | |||
Case08 | train | 40 | 512 | 512 | |||
Case09 | train | 47 | 512 | 512 | |||
Case10 | train | 39 | 512 | 512 | |||
Case11 | train | 45 | 512 | 512 | |||
Case12 | train | 46 | 512 | 512 | |||
Case13 | train | 15 | 320 | 320 | |||
Case14 | train | 20 | 320 | 320 | |||
Case15 | train | 20 | 320 | 320 | |||
Case16 | train | 20 | 320 | 320 | |||
Case17 | train | 20 | 320 | 320 | |||
Case18 | train | 17 | 320 | 320 | |||
Case19 | train | 20 | 320 | 320 | |||
Case20 | train | 20 | 320 | 320 | |||
Case21 | train | 20 | 320 | 320 | |||
Case22 | train | 20 | 320 | 320 | |||
Case23 | train | 20 | 320 | 320 | |||
Case24 | train | 20 | 320 | 320 | |||
Case25 | train | 18 | 256 | 256 | |||
Case26 | train | 23 | 512 | 512 | |||
Case27 | train | 23 | 512 | 512 | |||
Case28 | train | 23 | 512 | 512 | |||
Case29 | train | 23 | 512 | 512 | |||
Case30 | train | 23 | 512 | 512 | |||
Case31 | train | 23 | 512 | 512 | |||
Case32 | train | 23 | 512 | 512 | |||
Case33 | train | 23 | 512 | 512 | |||
Case34 | train | 28 | 384 | 384 | |||
Case35 | train | 23 | 256 | 256 | |||
Case36 | train | 26 | 512 | 512 | |||
Case37 | train | 28 | 320 | 320 | |||
Case38 | train | 24 | 320 | 320 | |||
Case39 | train | 24 | 320 | 320 | |||
Case40 | train | 24 | 320 | 320 | |||
Case41 | train | 24 | 320 | 320 | |||
Case42 | train | 24 | 320 | 320 | |||
Case43 | train | 24 | 320 | 320 | |||
Case44 | train | 24 | 320 | 320 | |||
Case45 | train | 24 | 320 | 320 | |||
Case46 | train | 24 | 320 | 320 | |||
Case47 | train | 24 | 320 | 320 | |||
Case48 | train | 24 | 320 | 320 | |||
Case49 | train | 24 | 320 | 320 |
PROMISE12: Prostate MR Image Segmentation 2012
Transverse T2-weighted prostate MRI volumes from the MICCAI 2012 Grand Challenge for whole-gland prostate segmentation. Contributions from 4 clinical centers.
Dataset Details
| Property | Value |
|---|---|
| Modality | MRI (T2-weighted, transverse) |
| Organ | Prostate (whole gland) |
| Total cases | 50 (training only — see below) |
| Format | MetaImage (.mhd header + .raw binary) |
| Image dtype | int16 (MET_SHORT) |
| Mask dtype | int8 (MET_CHAR), binary {0, 1} |
| In-plane size | 512 × 512 |
| Slices per volume | 15 – 54 |
Scope of This Upload
The original PROMISE12 challenge released 100 cases:
- 50 Training — public images and ground-truth masks (this upload)
- 30 Test — images released, ground-truth was withheld (challenge-closed, not included here)
- 20 Live Challenge — images released, ground-truth was withheld (not included here)
Only the 50 training cases have publicly available masks, so this repository contains those 50 paired volumes. The original challenge is closed and online scoring of test/live predictions is no longer available.
Multi-Center Composition
Each contributing center provided 25 of the 100 original cases. The 50 training cases here are a mix from these centers:
| Center | Institution | Field | Endorectal Coil | Vendor |
|---|---|---|---|---|
| RUNMC | Radboud Univ. Nijmegen Medical Centre, NL | 3T | No | Siemens |
| BIDMC | Beth Israel Deaconess Medical Center, USA | 3T | Yes | GE |
| UCL | University College London, UK | 1.5T & 3T | No | Siemens |
| HK | Haukeland Univ. Hospital, Norway | 1.5T | Yes | Siemens |
Note: The BIDMC contribution here is a distinct subset from the MedOtter/BIDMC dataset (which is the FedDG Multi-Site Prostate MRI collection containing 12 BIDMC cases).
File Structure
Each case has 4 files (image + mask, each MetaImage .mhd header + .raw binary):
CaseXX.mhd # T2 MRI volume header (references CaseXX.raw)
CaseXX.raw # T2 MRI voxel data (int16)
CaseXX_segmentation.mhd # Prostate mask header (references CaseXX_segmentation.raw)
CaseXX_segmentation.raw # Binary prostate mask (uint8, {0, 1})
50 cases total: Case00 through Case49.
Ground Truth
Masks were contoured slice-by-slice by an experienced reader at each contributing center using 3DSlicer or MeVisLab (spline-connected points), then independently validated and corrected by a second expert reviewer. This is the only mask source publicly distributed.
A second-observer mask (used in the original paper to establish inter-observer variability) exists for the test/live cases but is not part of this release.
Loading Example
import SimpleITK as sitk
image = sitk.GetArrayFromImage(sitk.ReadImage("Case00.mhd")) # (Z, Y, X) int16
mask = sitk.GetArrayFromImage(sitk.ReadImage("Case00_segmentation.mhd")) # (Z, Y, X) uint8
print(image.shape, mask.shape)
Citation
@article{litjens2014promise12,
title = {Evaluation of prostate segmentation algorithms for {MRI}: the {PROMISE12} challenge},
author = {Litjens, Geert and Toth, Robert and van de Ven, Wendy and Hoeks, Caroline and
Kerkstra, Sjoerd and van Ginneken, Bram and Vincent, Graham and Guillard, Gwenael and
Birbeck, Neil and Zhang, Jindang and Strand, Robin and Malmberg, Filip and Ou, Yangming and
Davatzikos, Christos and Kirschner, Matthias and Jung, Florian and Yuan, Jing and
Qiu, Wu and Gao, Qiang and Edwards, Philip Eddie and Maan, Bianca and
van der Heijden, Ferdinand and Ghose, Soumya and Mitra, Jhimli and Dowling, Jason and
Barratt, Dean and Huisman, Henkjan and Madabhushi, Anant},
journal = {Medical Image Analysis},
volume = {18},
number = {2},
pages = {359--373},
year = {2014},
doi = {10.1016/j.media.2013.12.002}
}
Sources
- Zenodo mirror: https://zenodo.org/records/8014041 (DOI: 10.5281/zenodo.8014041)
- Original portal: https://promise12.grand-challenge.org/
License
Custom 'Other (Attribution)': research use with mandatory citation of doi:10.1016/j.media.2013.12.002 (Zenodo 8026660 LICENSE.TXT)
Redistribution is permitted for non-commercial research use under the terms below; commercial use is not.
Source of the terms: https://zenodo.org/records/8026660
Audit note (verbatim from the MedOtter dataset card):
2026-09-06 adjudication (settles the audit CSV's action_needed / conditional): Zenodo record 8026660 (access_right open, licence 'Other (Attribution)') ships the data with a two-sentence LICENSE.TXT: 'You can use this data for your research. If you do that it is mandatory to cite https://doi.org/10.1016/j.media.2013.12.002.' The grant is a research-use grant with a mandatory citation; it neither forbids nor names redistribution, and the depositors published the data open-access under an attribution licence, so a mirror that carries LICENSE.TXT and the mandatory citation is read as permitted for research use: redistribution yes_noncommercial, commercial use no ('for your research' bounds the grant). The mirror carries the 50 training cases with LICENSE.TXT (verified 2026-09-06). Supersedes the audit CSV row.
Please cite:
Litjens, G., van Ginneken, B., Huisman, H., van de Ven, W., Hoeks, C., Barratt, D., & Madabhushi, A. (2014). Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge. Medical Image Analysis, 18(2), 359–373. https://doi.org/10.1016/j.media.2013.12.002
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