Training Data

Five datasets are provided with manual segmentations to use as training data to tune your segmentation algorithm. Manual segmentations (ground truth) were drawn on the thick-slice scans (3mm slice thickness), using an in-house developed manual segmentation tool based on the contour segmentation objects (CSO) tool available in Mevislab. A freehand spline drawing technique was used to segment all structures in the brain. The outline of each structure was delineated, starting with the innermost structures. By iteratively subtracting delineations to create holes, binary images were created for each structure. Segmentations were performed in a darkened room with optimal viewing conditions. All segmentations were inspected for correctness by an expert not involved in the segmentation procedure and corrections were made if needed. A third expert approved all final segmentations.

The following structures are manually segmented and will be available for training:

    1. Cortical gray matter
    2. Basal ganglia
    3. White matter
    4. White matter lesions
    5. Cerebrospinal fluid in the extracerebral space
    6. Ventricles
    7. Cerebellum
    8. Brainstem

The numbers in front of the structures indicate the labels in the ground truth image. Background will be labeled as 0. When your algorithm only uses gray matter, white matter and cerebrospinal fluid labels, you should merge labels 1 and 2, 3 and 4, and 5 and 6 yourself.

Notes on the manual segmentations

  • White matter lesions were segmented on the FLAIR scan.
  • The outer border of the CSF was segmented using both the T1-weighted scan and the T1-weighted IR scan.
  • All other structures were segmented on the T1-weighted scan (0.958mm×0.958mm×3.0mm).
  • Vessels were not segmented separately. The CSF segmentation therefore also includes the superior sagittal sinus and transverse sinuses.
  • The cerebral falx is also included in the CSF segmentation.

Test Data

The remaining 15 scans are provided as test data. Only the scans are provided, not the manual segmentations. Authors can submit the segmentation results of their algorithms, after which the evaluation results will be sent to them by e-mail. The results will be published on this website in the results section. Segmented tissue should be labeled as follows:

  1. Background (everything outside the brain)
  2. Cerebrospinal fluid (including ventricles)
  3. Gray matter (cortical gray matter and basal ganglia)
  4. White matter (including white matter lesions)

Your submission should be one image with the voxels labeled as described above. If your algorithm segments substructures (e.g. basal ganglia or ventricles), you should assign them to one of the above classes (1-3). The brainstem and cerebellum will be excluded from the evaluation. Your submission should be written in the ITK MetaImage format (mhd and raw files) or Nifti format (*.nii for matlab users). The ITK MetaImage format consists of a text file with “mhd” extension that contains the ASCII header information and a binary file with “raw” extension that contains the voxel data.

Please note that your result file should have the thick slice resolution (voxel size: 0.958mm×0.958mm×3.0mm), since the ground truth is only available for the thick slice data!