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image imagewidth (px) 512 512 | label class label 6
classes |
|---|---|
0ct_hemorrhage | |
0ct_hemorrhage | |
1ct_normal | |
1ct_normal | |
1ct_normal | |
2glioma | |
2glioma | |
2glioma | |
2glioma | |
2glioma | |
2glioma | |
2glioma | |
2glioma | |
3healthy | |
3healthy | |
3healthy | |
3healthy | |
3healthy | |
4meningioma | |
4meningioma | |
4meningioma | |
4meningioma | |
4meningioma | |
4meningioma | |
5pituitary | |
5pituitary | |
5pituitary | |
5pituitary | |
5pituitary | |
5pituitary |
NeuroSAM3 Sample Dataset
Curated sample images for testing the NeuroSAM3 agentic neuroimaging platform.
Contents
| Category | Count | Modality | Description |
|---|---|---|---|
| glioma | 8 | MRI T1w | Glioma brain tumors |
| meningioma | 6 | MRI T1w | Meningioma (extra-axial) |
| pituitary | 6 | MRI T1w | Pituitary adenomas |
| healthy | 5 | MRI T1/T2 | Normal brain anatomy |
| ct_normal | 3 | CT | Normal brain CT |
| ct_hemorrhage | 2 | CT | Intracranial hemorrhage |
Usage
These images are loaded on-demand by the NeuroSAM3 app via the sample_data.py module.
from sample_data import load_sample_image, load_category_batch
# Load single sample
path = load_sample_image("glioma", index=1)
# Load all gliomas for batch analysis
paths = load_category_batch("glioma")
Sources
Inspired by:
- Figshare brain_tumor_dataset (Cheng, 2017)
- Kaggle brain-mri-scans
License
CC-BY-SA 4.0
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