Data · dataset · 2026
Tlemcen-NeuroOncMRI: A Clinically Annotated Multisequence Brain MRI Dataset with Patient-Level Metadata for Primary and Secondary Tumor Classification from Algeria
Listed in Teesside University Research Data Repository
Tlemcen-NeuroOncMRI is a clinically annotated, patient-linked brain MRI dataset collected retrospectively at the Anti-Cancer Center of Tlemcen, Algeria.
Description
It includes 45 independent patients, with 28 primary brain tumor (PBT) cases and 17 cerebral metastasis (CM) cases, for a total of 19,009 MRI images. The resource also provides patient-level metadata and one de-identified French-language clinical imaging report per patient.
MRI examinations were acquired at multiple external imaging centres, with heterogeneous acquisition protocols and sequence availability. A clinically curated subset of 2,393 images (1,334 PBT and 1,059 CM) was used for the companion patient-level benchmark. Because multiple images originate from the same patient, all machine-learning experiments should use patient-level splitting to avoid data leakage; random slice-level splitting is not recommended.
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The dataset is intended for brain tumor classification, transfer learning, multimodal MRI-report modeling, radiomics, weakly supervised learning, and reproducibility studies. It does not include voxel-level segmentation masks. All data were anonymized before release, and users must not attempt to re-identify participants.
Links
Where it is published
- DOI doi.org/10.17632/9ns6748zkc.2 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Artificial intelligence · Computer Science & AI · Earth & Environmental Science · Medicine & Health
- Inferred from text
- Cancer 65% · Image 65% · Imaging 75% · Magnetic resonance imaging 65%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/9ns6748zkc.2 | 14 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[disease].local:disease:cancer | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[field].anzsrc:group:4602 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Artificial Intelligence'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:image | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[modality].local:modality:imaging | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:mri | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |