Adding mini skm-tea dataset to hub

README.md

@@ -1,3 +1,35 @@
 ---
+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}
+}
+```

v1-release/all_metadata.csv

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+,MTR_ID,PatientID,Timepoint,PatientAge,PatientSex,Scanner,Sequence,SliceThickness,SliceSpacing,Is_ZIP2,Ext_ID,SpoilerGradientArea,SpoilerGradientTime,ZIP2_kz1,ZIP2_kz2,Modality,SeriesDescription,ScanningSequence,SequenceVariant,RepetitionTime,EchoTime1,NumberOfAverages,ImagingFrequency,ImagedNucleus,EchoNumbers,MagneticFieldStrength,SpacingBetweenSlices,EchoTrainLength,PercentSampling,PercentPhaseFieldOfView,PixelBandwidth,DeviceSerialNumber,ProtocolName,ReconstructionDiameter,ReceiveCoilName,TransmitCoilName,FlipAngle,VariableFlipAngleFlag,SAR,PatientPosition,WindowCenter,WindowWidth,MedialDirection
+0,MTR_030,249,0,52,F,2,mfastDessMaps,1.6,0.8,True,MTR_030,3132,2392,80,80,MR,Sag DESS Low 3132,RM,NONE,20.36,6.428,1.0,127.963751,1H,1,3,0.799998,1,100,100,162.773,Anonymized,Anonymized,160,HD TR Knee PA,HD TR Knee PA,20,N,0.00503966,FFS,2083,4167,R
+1,MTR_184,0,0,58,M,2,mfastDessMaps,1.6,0.8,True,MTR_184,3132,2392,80,80,MR,Sag DESS Low 3132,RM,NONE,20.36,6.428,1.0,127.96382,1H,1,3,0.799997,1,100,100,162.773,Anonymized,Anonymized,160,HD TR Knee PA,HD TR Knee PA,20,N,0.00382117,FFS,2257,4515,R
+2,MTR_201,225,0,72,M,1,mfastDessMaps,1.6,0.8,True,MTR_201,3132,1488,80,80,MR,Sag DESS Low 3132,RM,NONE,18.352,5.876,1.0,127.720633,1H,1,3,0.8,1,100,100,162.773,Anonymized,Anonymized,160,HD TR Knee PA,HD TR Knee PA,20,N,0.00440602,FFS,1564,3129,L
+3,MTR_230,238,0,62,M,1,mfastDessMaps,1.6,0.8,True,MTR_230,3132,1488,80,80,MR,Sag DESS Low 3132,RM,NONE,18.352,5.876,1.0,127.720556,1H,1,3,0.800001,1,100,100,162.773,Anonymized,Anonymized,160,HD TR Knee PA,HD TR Knee PA,20,N,0.00453606,FFS,1988,3976,L

v1-release/annotations/v1.0.0/test.json

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v1-release/annotations/v1.0.0/train.json

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+}

v1-release/annotations/v1.0.0/val.json

@@ -0,0 +1,323 @@
+{
+  "info": {
+    "contributor": "Arjun Desai, Elka Rubin, Andrew Schmidt, Akshay Chaudhari & collaborators",
+    "description": "2021 SKM-TEA Dataset - val",
+    "year": "2021",
+    "date_created": "2021-08-23 14:05:06 PST",
+    "version": "v1.0.0"
+  },
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+      "name": "Meniscal Tear (Horizontal)"
+    },
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+      "id": 3,
+      "name": "Meniscal Tear (Radial)"
+    },
+    {
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+      "name": "Meniscal Tear (Vertical/Longitudinal)"
+    },
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+    },
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