mlinslab/neurobench

Directory	Contents
data/	Image files in both NIfTI and preprocessed tensor formats
neuro_vl_assets/	Neuro-VL-generated baseline reports
zeroshot_classification/	CSVs for study-level diagnostic classification
visual_question_answering/closed_ended/	CSVs for multiple-choice and yes/no questions
visual_question_answering/report_generation/	CSVs for report generation
visual_question_answering/red_team/	CSVs for red-team evaluations

Download preprocessed image tensors.

from pathlib import Path
from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="mlinslab/neurobench",
    repo_type="dataset",
    allow_patterns="data/tensor/**",
    local_dir="./neurobench_data",
)

root = Path("./neurobench_data/data/tensor/rsna")
for batch in root.glob("batch_[0-4]"):
    for patient in batch.iterdir():
        patient.rename(root / patient.name)
    batch.rmdir()

Alternatively, you can download raw images in NIfTI format (img.nii.gz or img.nii):

from pathlib import Path
from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="mlinslab/neurobench",
    repo_type="dataset",
    allow_patterns="data/nifti/**",
    local_dir="./neurobench_data",
)

root = Path("./neurobench_data/data/nifti/rsna")
for batch in root.glob("batch_[0-4]"):
    for patient in batch.iterdir():
        patient.rename(root / patient.name)
    batch.rmdir()

For Neuro-VL preprocessing details, see this script. For inference and evaluation instructions, see Neuro-VL repo and NeuroBench repo.