MICCAI 2015 Challenge on Multimodal Brain Tumor Segmentation (BraTS2015)

BRATS2015 (1812 files)
training/LGG/brats_tcia_pat346_0001/VSD.Brain_3more.XX.O.OT.42599.mha 8.93MB
training/LGG/brats_tcia_pat346_0001/VSD.Brain.XX.O.MR_T2.41041.mha 2.53MB
training/LGG/brats_tcia_pat346_0001/VSD.Brain.XX.O.MR_T1c.41042.mha 2.54MB
training/LGG/brats_tcia_pat346_0001/VSD.Brain.XX.O.MR_T1.41043.mha 2.49MB
training/LGG/brats_tcia_pat346_0001/VSD.Brain.XX.O.MR_Flair.41040.mha 2.33MB
training/LGG/brats_tcia_pat330_0001/VSD.Brain_3more.XX.O.OT.42585.mha 8.93MB
training/LGG/brats_tcia_pat330_0001/VSD.Brain.XX.O.MR_T2.41027.mha 2.25MB
training/LGG/brats_tcia_pat330_0001/VSD.Brain.XX.O.MR_T1c.41028.mha 2.24MB
training/LGG/brats_tcia_pat330_0001/VSD.Brain.XX.O.MR_T1.41029.mha 2.22MB
training/LGG/brats_tcia_pat330_0001/VSD.Brain.XX.O.MR_Flair.41026.mha 2.08MB
training/LGG/brats_tcia_pat325_0001/VSD.Brain_3more.XX.O.OT.42581.mha 8.93MB
training/LGG/brats_tcia_pat325_0001/VSD.Brain.XX.O.MR_T2.36006.mha 2.29MB
training/LGG/brats_tcia_pat325_0001/VSD.Brain.XX.O.MR_T1c.36007.mha 2.29MB
training/LGG/brats_tcia_pat325_0001/VSD.Brain.XX.O.MR_T1.36008.mha 2.21MB
training/LGG/brats_tcia_pat325_0001/VSD.Brain.XX.O.MR_Flair.36005.mha 2.10MB
training/LGG/brats_tcia_pat312_0001/VSD.Brain_3more.XX.O.OT.42557.mha 8.93MB
training/LGG/brats_tcia_pat312_0001/VSD.Brain.XX.O.MR_T2.35982.mha 2.24MB
training/LGG/brats_tcia_pat312_0001/VSD.Brain.XX.O.MR_T1c.35983.mha 2.15MB
training/LGG/brats_tcia_pat312_0001/VSD.Brain.XX.O.MR_T1.35984.mha 2.14MB
training/LGG/brats_tcia_pat312_0001/VSD.Brain.XX.O.MR_Flair.35981.mha 2.21MB
training/LGG/brats_tcia_pat307_0001/VSD.Brain_3more.XX.O.OT.42539.mha 8.93MB
training/LGG/brats_tcia_pat307_0001/VSD.Brain.XX.O.MR_T2.40972.mha 2.34MB
training/LGG/brats_tcia_pat307_0001/VSD.Brain.XX.O.MR_T1c.40973.mha 2.36MB
training/LGG/brats_tcia_pat307_0001/VSD.Brain.XX.O.MR_T1.40974.mha 2.29MB
training/LGG/brats_tcia_pat307_0001/VSD.Brain.XX.O.MR_Flair.40971.mha 2.04MB
training/LGG/brats_tcia_pat299_0001/VSD.Brain_3more.XX.O.OT.42531.mha 8.93MB
training/LGG/brats_tcia_pat299_0001/VSD.Brain.XX.O.MR_T2.35953.mha 2.09MB
training/LGG/brats_tcia_pat299_0001/VSD.Brain.XX.O.MR_T1c.35954.mha 1.91MB
training/LGG/brats_tcia_pat299_0001/VSD.Brain.XX.O.MR_T1.35955.mha 1.91MB
training/LGG/brats_tcia_pat299_0001/VSD.Brain.XX.O.MR_Flair.35952.mha 1.92MB
training/LGG/brats_tcia_pat298_0001/VSD.Brain_3more.XX.O.OT.42529.mha 8.93MB
training/LGG/brats_tcia_pat298_0001/VSD.Brain.XX.O.MR_T2.35949.mha 1.90MB
training/LGG/brats_tcia_pat298_0001/VSD.Brain.XX.O.MR_T1c.35950.mha 1.75MB
training/LGG/brats_tcia_pat298_0001/VSD.Brain.XX.O.MR_T1.35951.mha 1.76MB
training/LGG/brats_tcia_pat298_0001/VSD.Brain.XX.O.MR_Flair.35948.mha 1.74MB
training/LGG/brats_tcia_pat282_0001/VSD.Brain_3more.XX.O.OT.42507.mha 8.93MB
training/LGG/brats_tcia_pat282_0001/VSD.Brain.XX.O.MR_T2.40944.mha 2.19MB
training/LGG/brats_tcia_pat282_0001/VSD.Brain.XX.O.MR_T1c.40945.mha 2.21MB
training/LGG/brats_tcia_pat282_0001/VSD.Brain.XX.O.MR_T1.40946.mha 2.15MB
training/LGG/brats_tcia_pat282_0001/VSD.Brain.XX.O.MR_Flair.40943.mha 1.99MB
training/LGG/brats_tcia_pat276_0001/VSD.Brain_3more.XX.O.OT.42497.mha 8.93MB
training/LGG/brats_tcia_pat276_0001/VSD.Brain.XX.O.MR_T2.35903.mha 2.36MB
training/LGG/brats_tcia_pat276_0001/VSD.Brain.XX.O.MR_T1c.35904.mha 2.33MB
training/LGG/brats_tcia_pat276_0001/VSD.Brain.XX.O.MR_T1.35905.mha 2.23MB
training/LGG/brats_tcia_pat276_0001/VSD.Brain.XX.O.MR_Flair.35902.mha 2.14MB
training/LGG/brats_tcia_pat266_0001/VSD.Brain_3more.XX.O.OT.42493.mha 8.93MB
training/LGG/brats_tcia_pat266_0001/VSD.Brain.XX.O.MR_T2.35889.mha 2.28MB
training/LGG/brats_tcia_pat266_0001/VSD.Brain.XX.O.MR_T1c.35890.mha 2.26MB
training/LGG/brats_tcia_pat266_0001/VSD.Brain.XX.O.MR_T1.35891.mha 2.19MB
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Type: Dataset
Tags:

Bibtex:
@article{,
title= {MICCAI 2015 Challenge on Multimodal Brain Tumor Segmentation (BraTS2015)},
keywords= {},
journal= {},
author= {},
year= {2015},
url= {http://braintumorsegmentation.org/},
license= {Creative Commons Attribution-NonCommercial 3.0 license. (CC BY NC SA 3.0)},
abstract= {Brain tumor image data used in this article were obtained from the MICCAI Challenge on Multimodal Brain Tumor Segmentation. The challenge database contain fully anonymized images from the Cancer Imaging Archive.


1 for necrosis

2 for edema

3 for non-enhancing tumor

4 for enhancing tumor

0 for everything else
    
```
here are 3 requirements for the successfull upload and validation of your segmentation:
Use the MHA filetype to store your segmentations (not mhd) [use short or ushort if you experience any upload problems]
Keep the same labels as the provided truth.mha (see above)
Name your segmentations according to this template: VSD.your_description.###.mha 
replace the ### with the ID of the corresponding Flair MR images. This allows the system to relate your segmentation to the correct training truth. Download an example list for the training data and testing data.
```

![](https://i.imgur.com/umg5BKD.png)

### Publications

B. H. Menze et al., "The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)," in IEEE Transactions on Medical Imaging, vol. 34, no. 10, pp. 1993-2024, Oct. 2015.
doi: 10.1109/TMI.2014.2377694
http://ieeexplore.ieee.org/document/6975210/

Kistler et. al, The virtual skeleton database: an open access repository for biomedical research and collaboration. JMIR, 2013.},
superseded= {},
terms= {}
}


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