| language: en | |
| license: other | |
| tags: | |
| - mri | |
| - quantitative mri | |
| - reconstruction | |
| - segmentation | |
| - detection | |
| # SKM-TEA Sample Data | |
| This dataset consists of a subset of scans from the [SKM-TEA dataset](https://arxiv.org/abs/2203.06823). It can be used to build tutorials / demos with the SKM-TEA dataset. | |
| To access to the full dataset, please follow instructions on [Github](https://github.com/StanfordMIMI/skm-tea/blob/main/DATASET.md). | |
| **NOTE**: This dataset subset *should not* be used for reporting/publishing metrics. All metrics should be computed on the full SKM-TEA test split. | |
| ## Details | |
| This mini dataset (~30GB) consists of 2 training scans, 1 validation scan, and 1 test scan from the SKM-TEA dataset. HDF5 files for the Raw Data Track are [lzf-compressed](http://www.h5py.org/lzf/) to reduce size while maximizing speed for decompression. | |
| ## License | |
| By using this dataset, you agree to the [Stanford University Dataset Research Use Agreement](https://stanfordaimi.azurewebsites.net/datasets/4aaeafb9-c6e6-4e3c-9188-3aaaf0e0a9e7). | |
| ## Reference | |
| If you use this dataset, please reference the SKM-TEA paper: | |
| ``` | |
| @inproceedings{ | |
| desai2021skmtea, | |
| title={{SKM}-{TEA}: A Dataset for Accelerated {MRI} Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation}, | |
| author={Arjun D Desai and Andrew M Schmidt and Elka B Rubin and Christopher Michael Sandino and Marianne Susan Black and Valentina Mazzoli and Kathryn J Stevens and Robert Boutin and Christopher Re and Garry E Gold and Brian Hargreaves and Akshay Chaudhari}, | |
| booktitle={Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2)}, | |
| year={2021}, | |
| url={https://openreview.net/forum?id=YDMFgD_qJuA} | |
| } | |
| ``` | |