@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superseded= {},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= {}
}