Skip to content
MRI Brain

Vestibular-Schwannoma-SEG

Segmentation of Vestibular Schwannoma from Magnetic Resonance Imaging: An Open Annotated Dataset and Baseline Algorithm

Gamma Knife planning MRI (contrast-enhanced T1 and high-resolution T2) of 242 patients with a unilateral vestibular schwannoma from one London centre, with manual tumour and cochlea contours, RT dose, plan and structure files and T1-T2 registration matrices.

Overview

Vestibular-Schwannoma-SEG holds the radiosurgery planning MRI of 242 adults with a single unilateral vestibular schwannoma, treated with Gamma Knife stereotactic radiosurgery at the Queen Square Radiosurgery Centre in London between October 2012 and January 2018. It was released on The Cancer Imaging Archive by a King's College London and UCL group as the training data of their published 2.5D attention U-Net, and is used to develop and test automatic tumour segmentation and volumetry. The radiotherapy objects also support organ-at-risk contouring and dose planning.

Composition

Each patient has one session with a contrast-enhanced T1-weighted scan and a high-resolution T2-weighted scan, plus the RT structure set, RT plan and RT dose for each of the two images, giving 1,936 DICOM series and 48,582 images. Patients are 147 women and 95 men with a median age of 56 (range 24 to 84). Forty-nine had prior surgery for the tumour. Median tumour volume is 1.36 cm³. Version 2 added ITK affine matrices for T1-T2 co-registration and the original contour points as JSON. The paper's code splits the cohort at random into 176 training, 20 tuning and 46 test patients.

Acquisition

Scans were acquired on the day of, or shortly before, treatment with the head fixed in a Leksell stereotactic frame, whose fiducials drive the T1-T2 registration. The paper states a Siemens Avanto 1.5 T with a single-channel head coil, an MPRAGE-type T1 at 0.4 mm in-plane resolution and a 3D CISS T2 at about 0.5 mm in-plane, slices 1.0 to 1.5 mm. Faces were masked with a de-facing algorithm.

Annotations

The tumour, and for some patients organs at risk such as the cochlea and brainstem, were contoured slice by slice in Leksell GammaPlan in consensus by the treating neurosurgeon, neuroradiologist and physicist. The tumour was usually drawn on T1 and refined on T2; the cochlea usually on T2. The RTSTRUCT contours are interpolated by GammaPlan, while the JSON files keep the original, uninterpolated contours.

Known limitations

  • Single centre; all scans follow planning protocols, not routine surveillance MRI.
  • Rasterising the interpolated RTSTRUCT contours can drop the top and bottom tumour slices.
  • Sources disagree on details: the paper names only the Avanto 1.5 T and CISS, the collection page also mentions FIESTA, and the series metadata lists five patients with TrioTim or Prisma_fit model names. The exclusion counts also differ between the paper and the collection page.

Cohort

Aggregate numbers from the sources below. Bars are relative to the 242 subjects.

Sex

  • Female 147 61%
  • Male 95 39%

Age

mean 55.5± 12.7 · range 24 to 84
0
20
40
60
72
20-2930-3940-4950-5960-6970-7980+

Contrast combinations

How many subjects have exactly each set of contrasts.

T1w_ceT2wSubjects with exactly this set
242

Modality

scans

  • MRI 484 25%

Contrast / sequence

subjects, values can overlap

  • T1-weighted, contrast enhanced 242 100%
  • T2-weighted 242 100%

Condition

subjects, values can overlap

  • Vestibular schwannoma 242 100%

Scanner vendor

subjects

  • Siemens Healthineers 242 100%

Split

subjects

  • Training 176 73%
  • Test 46 19%
  • Validation 20 8%

License and access

Our reading of the license, not legal advice. Before you use the data, read the original license and confirm that your use is allowed. We take no responsibility for how you use a dataset. Full disclaimer

Access
Open download

Download without an account

DICOM images and RT objects via the TCIA Data Retriever; registration matrices, JSON contours and the directory name mapping as direct downloads. Scripts to convert the data to NIfTI are at https://github.com/KCL-BMEIS/VS_Seg.

Access page

Creative Commons Attribution 4.0 International

Use, share and adapt the data for any purpose, including commercial use, as long as you credit the creators.

Every item on the TCIA collection page is listed under CC BY 4.0. TCIA also asks users to follow its Data Usage Policy and Restrictions and to cite the dataset DOI.

Original license text Version read: 4.0 Checked 2026-10-07

What you can do

  • Yes
  • Yes
  • Yes
  • Yes

What you can share

  • Yes
  • Yes
  • Yes

What you must do

  • Yes
  • Share alike No
  • No
  • No
  • Manuscript review No
  • Release code No
  • Return results No
  • Delete after use No

Limits

  • No
  • Location limits No

Citation

Shapey J, Kujawa A, Dorent R, et al. Segmentation of vestibular schwannoma from MRI, an open annotated dataset and baseline algorithm. Scientific Data 8, 286 (2021). https://doi.org/10.1038/s41597-021-01064-w. Data: Shapey J, Kujawa A, Dorent R, et al. (2021). Segmentation of Vestibular Schwannoma from Magnetic Resonance Imaging: An Open Annotated Dataset and Baseline Algorithm (version 2) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.9YTJ-5Q73

All numbers

Every number on this page, as stored in stats.csv, with its source.

MeasureBreakdownValueSource
Subjectstotal
consecutive patients treated with Gamma Knife radiosurgery
242shapey2021
Methods, Data overview
Subjectscondition=vestibular_schwannoma
single unilateral sporadic vestibular schwannoma
242shapey2021
Methods, Data overview
Studiestotal
one planning MRI session per patient
242tcia-vestibular-schwannoma-seg
Data Access (Version 2)
Scanstotal
DICOM series, including RTDOSE, RTSTRUCT and RTPLAN objects
1,936tcia-vestibular-schwannoma-seg
Data Access (Version 2)
Imagestotal
DICOM image files
48,582tcia-vestibular-schwannoma-seg
Data Access (Version 2)
Scansmodality=MR
MR image sets
484shapey2021
Methods, Data overview
Subjectssex=female 147shapey2021
Methods, Data overview
Subjectssex=male 95shapey2021
Methods, Data overview
Median agetotal 56shapey2021
Methods, Data overview
Minimum agetotal 24shapey2021
Methods, Data overview
Maximum agetotal 84shapey2021
Methods, Data overview
Mean agetotal 55.5tcia-vestibular-schwannoma-seg-digest
Patient ID, Patient Age
Age SDtotal 12.7tcia-vestibular-schwannoma-seg-digest
Patient ID, Patient Age
Subjectsage=20-29 6tcia-vestibular-schwannoma-seg-digest
Patient ID, Patient Age
Subjectsage=30-39 27tcia-vestibular-schwannoma-seg-digest
Patient ID, Patient Age
Subjectsage=40-49 38tcia-vestibular-schwannoma-seg-digest
Patient ID, Patient Age
Subjectsage=50-59 72tcia-vestibular-schwannoma-seg-digest
Patient ID, Patient Age
Subjectsage=60-69 68tcia-vestibular-schwannoma-seg-digest
Patient ID, Patient Age
Subjectsage=70-79 27tcia-vestibular-schwannoma-seg-digest
Patient ID, Patient Age
Subjectsage=80+ 4tcia-vestibular-schwannoma-seg-digest
Patient ID, Patient Age
Subjectscontrast=T1w_ce 242shapey2021
Methods, Data overview
Subjectscontrast=T2w
high-resolution T2 (3D CISS)
242shapey2021
Methods, Data overview
Subjectscontrast_set=T1w_ce+T2w 242shapey2021
Methods, Data overview
Scanscontrast=T1w_ce 242tcia-vestibular-schwannoma-seg-digest
Modality, Series Description
Scanscontrast=T2w 242tcia-vestibular-schwannoma-seg-digest
Modality, Series Description
Subjectsvendor=siemens 242tcia-vestibular-schwannoma-seg-digest
Patient ID, Modality, Manufacturer
Subjectssplit=train
random split used for the released baseline algorithm
176shapey2021
Code availability
Subjectssplit=validation
hyperparameter tuning set of the baseline algorithm
20shapey2021
Code availability
Subjectssplit=test
test set of the baseline algorithm
46shapey2021
Code availability

Sources

The keys used in the table above.