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UCSF-PDGM Test Subset (VQA Demo)

A three-study subset of the UCSF Preoperative Diffuse Glioma MRI (UCSF-PDGM) dataset, mirrored here as test fixtures for a web-based visual question answering (VQA) demo. The full source dataset is publicly available on The Cancer Imaging Archive (TCIA).

Contents

Three preoperative brain MRI studies from patients with diffuse glioma:

  • UCSF-PDGM-0159_nifti/
  • UCSF-PDGM-0338_nifti/
  • UCSF-PDGM-0529_nifti/

Each study folder contains multi-sequence NIfTI volumes (T1, T1c, T2, FLAIR, SWI, DWI, ADC, ASL, DTI derivatives) and segmentations (tumor, brain, brain parenchyma), following the original UCSF-PDGM file naming.

Purpose

These studies are loaded at runtime by a React/Vite frontend that demonstrates VQA on brain MRI, using NiiVue for browser-based 3D visualization. Hosting on Hugging Face avoids committing large NIfTI files to the GitHub repository while keeping the data accessible to the deployed web demo.

This subset is intended for demonstration and development only. It is not a benchmark, not a curated split, and not intended for training or evaluation of new models. Use the full UCSF-PDGM release for those purposes.

Source dataset

This is a mirror of three studies from the public UCSF-PDGM release. The data has not been modified.

Citation

If you use this data, please cite the original UCSF-PDGM publication:

Calabrese, E., Villanueva-Meyer, J. E., Rudie, J. D., Rauschecker, A. M., Baid, U., Bakas, S., Cha, S., Mongan, J. T., & Hess, C. P. (2022). The University of California San Francisco Preoperative Diffuse Glioma MRI (UCSF-PDGM). The Cancer Imaging Archive. https://doi.org/10.7937/tcia.bdgf-8v37

And the associated paper: Calabrese, E., Villanueva-Meyer, J. E., Rudie, J. D., et al. (2022). The University of California San Francisco Preoperative Diffuse Glioma MRI Dataset. Radiology: Artificial Intelligence, 4(6), e220058. https://doi.org/10.1148/ryai.220058

License

This subset is distributed under CC BY 4.0, inherited from the source UCSF-PDGM dataset.

Acknowledgements

UC Berkeley Capstone project conducted in collaboration with the UCSF Bakar Computational Precision Health Institute.

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