Brain MRI Glioma

This data set is part of the public development data for the 2023 Automated Universal Classification Challenge (AUC23). The data set concerns the prediction of the world health organization (WHO) subtype of patients with glioma in magnetic resonance imaging (MRI). The data set was previously introduced and described by van der Voort et al. (2021).Data was restructured in compliance with the AUC23 challenge format.

Images are 4D tensors:

0: T1-weighted,

1: post-contrast T1-weighted

2: T2-weighted

3: T2-weighted FLAIR

Classification labels:

0: WHO grade 2

1: WHO grade 3

2: WHO grade 4

imagesTr (root folder with all patients and studies)
    ├── whogliomagrade_0289_0000.mha  (4D MRI for study 289)
    ├── whogliomagrade_0505_0000.mha  (4D MRI for study 0505)
    ├── ...

Please cite the following data set if you are using the kidney CT abnormality data :

van der Voort SR, Incekara F, Wijnenga MMJ, Kapsas G, Gahrmann R, Schouten JW, Dubbink HJ, Vincent AJPE, van den Bent MJ, French PJ, Klein S, Smits M. The Erasmus Glioma Database (EGD): Structural MRI scans, WHO 2016 subtypes, and segmentations of 774 patients with glioma. Data Brief. 2021 Jun 2;37:107191. doi: 10.1016/j.dib.2021.107191. PMID: 34159239; PMCID: PMC8203723.