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MRI Brain

Radboudumc TBI SWI Microbleed Set

Radboudumc moderate-to-severe traumatic brain injury SWI cerebral microbleed dataset

Susceptibility-weighted brain MRI of patients with moderate to severe traumatic brain injury and controls, with microbleed segmentations, used to develop detectors of trauma-related microbleeds. 81 studies of 45 patients and 18 controls from one Dutch centre. Not publicly released.

Overview

This is an in-house MRI collection from Radboud University Medical Center in Nijmegen, the Netherlands, used to develop deep learning detectors of cerebral microbleeds after traumatic brain injury. In trauma, microbleeds are taken as a marker of traumatic axonal injury, and severe cases can show a hundred or more of them, often in clusters or with a curvilinear shape. The 2022 paper compares a patch classifier, a segmentation CNN and a 3D U-Net on these data.

Composition

The text describes 45 patients with moderate or severe TBI (Glasgow Coma Scale 3 to 12), 20 of them scanned at two timepoints, plus 18 healthy volunteers, for 81 MRI studies in total. Table 1 of the paper lists 46 TBI subjects across the splits, so the patient count differs by one between text and table. The studies are split into 45 for training (41 TBI, 4 control), 16 for validation (12 TBI, 4 control) and 20 for testing (10 TBI, 10 control). The data were collected retrospectively with a waiver of informed consent.

Acquisition

All scans come from one 3 T Siemens Magnetom Trio. Each study has an SWI scan (TR 27 ms, TE 20 ms, flip angle 15 degrees, 0.98 x 0.98 x 1.00 mm voxels) and a T1 MP-RAGE (1 mm isotropic). Only SWI is used by the deep learning models.

Annotations

Training and validation studies have voxel segmentations of the full blooming extent of each microbleed. An experienced neuroradiologist sorted the output of an earlier computer-aided detection system into definite, possible and false positive microbleeds and added missed ones, and a medical student then outlined each lesion under her supervision. For 10 test studies, six observers of differing experience placed points on definite and possible microbleeds; region growing from these points and a majority vote give the test reference. Agreement between observers was low (Fleiss' kappa 0.19 to 0.24).

Known limitations

  • Not publicly available. The paper announced a Zenodo release and a challenge, but neither could be found.
  • One scanner, one SWI protocol and one centre.
  • Only moderate and severe TBI; mild TBI is not included.
  • Small test set with low inter-observer agreement on what counts as a microbleed.

Cohort

Aggregate numbers from the sources below. Bars are relative to the 63 subjects.

Contrast / sequence

Studies

Groups can overlap

  • Susceptibility-weighted 81 100%
  • T1-weighted 81 100%

Section 2.1.1 and Table 2 in Koschmieder et al. 2022, NeuroImage Clinical (PMC9127224)

Scanner vendor

Studies
  • Siemens Healthineers 81 100%

Section 2.1.1 in Koschmieder et al. 2022, NeuroImage Clinical (PMC9127224)

Country

Studies
  • Netherlands 81 100%

Section 2.1.1 in Koschmieder et al. 2022, NeuroImage Clinical (PMC9127224)

Split by condition

Studies

Reported cross table. A dot marks a cell the source does not give.

Traumatic brain injuryHealthy control
Training41·
Test1010
Validation12·

Table 1 in Koschmieder et al. 2022, NeuroImage Clinical (PMC9127224)

Condition

Groups can overlap

  • Traumatic brain injury 45 71%
  • Healthy control 18 29%

Section 2.1.1 in Koschmieder et al. 2022, NeuroImage Clinical (PMC9127224)

Field strength

Studies
  • 3 T 81 100%

Section 2.1.1 in Koschmieder et al. 2022, NeuroImage Clinical (PMC9127224)

Split

Studies
  • Training 45 56%
  • Test 20 25%
  • Validation 16 20%

Abstract and Table 1 in Koschmieder et al. 2022, NeuroImage Clinical (PMC9127224)

Contrast combinations

Studies

How many studies have exactly each set of contrasts.

T1wswiSubjects with exactly this set
81

Section 2.1.1 in Koschmieder et al. 2022, NeuroImage Clinical (PMC9127224)

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
On request

Ask the authors or the data holder. No published process or terms, and access is at their discretion

Access page

No published license or data use terms

The data holder has published no license and no data use terms. Any use, sharing or commercial right has to be agreed with the data holder, and nothing can be assumed to be allowed. Default copyright and data protection law still apply.

The paper has no data availability statement. A footnote says the MRI data without the test set "will be made available on Zenodo (10.5281/zenodo.6535523)" for a challenge at traumatic-cmb.grand-challenge.org. On 2026-10-08 that DOI was not registered and the challenge site was not publicly reachable. The CC BY-NC-ND 4.0 license of the article covers the text only.

Original license text Checked 2026-10-08

What you can do

  • Commercial use Not stated
  • Not stated
  • Train ML models Not stated
  • Create derived data Not stated
  • Publish results Not stated

What you can share

  • Share the data Not stated
  • Share derived data Not stated
  • Share trained models Not stated

What you must do

  • Cite or credit Not stated
  • Share alike Not stated
  • Sign an agreement Not stated
  • Ethics approval Not stated
  • Manuscript review Not stated
  • Release code Not stated
  • Return results Not stated
  • Delete after use Not stated

Limits

  • No re-identification Not stated
  • Location limits Not stated

Citation

Koschmieder K, Paul MM, van den Heuvel TLA, van der Eerden AW, van Ginneken B, Manniesing R. Automated detection of cerebral microbleeds via segmentation in susceptibility-weighted images of patients with traumatic brain injury. NeuroImage: Clinical 35, 103027 (2022). doi:10.1016/j.nicl.2022.103027

Sources

Every number on this page comes from one of these documents. Each chart names the table or page it is taken from. The raw numbers are in stats.csv.