This is an active and ongoing medical image analysis challenge, welcoming new and updated submissions.


The purpose of this challenge is to directly compare methods for the automatic segmentation of White Matter Hyperintensities (WMH) of presumed vascular origin.


To participate in the challenge, interested teams can register on this website. After registration, training data can be downloaded. This data consists of 60 sets of brain MR images (T1 and FLAIR) with manual annotations of WMH (binary masks) from three different institutes / scanners. Manual annotations have been made by experts in WMH scoring.

Participants can train their methods on the available data and submit the resulting method for evaluation by the organizers. A brief description (1-2 pages) of the method should be included. Test data will not be released, but consists of 110 sets of brain MR images from five different scanners (of which three are also in the training data).


Initial results of this challenge have been published by IEEE Transactions on Medical Imaging. Please cite this paper in scientific output resulting from your participation: Kuijf, H. J., et al. “Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities; Results of the WMH Segmentation Challenge.” IEEE transactions on medical imaging (2019).


The kick-off meeting of this challenge was organized at MICCAI 2017 in Quebec, Canada. Initially, twenty teams participated and presented their method. The challenge remained open and is ongoing since then. These slides were presented during the challenge session at MICCAI 2017.

These presentations can be used under the Creative Commons Attribution 4.0 International License.