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Model parameters

  • Task: Team K2's solution for WMH segmentation grand challenge (http://wmh.isi.uu.nl/) at MICCAI 2017.
  • Imaging modality: MRI
  • Organ: Brain
  • Input(s): Brain Axial T1-W MRI and FLAIR
  • Output(s): White matter hyperintensities binary segmentation maps
  • Training set size: 60 / Test set size: 110
  • Performance: Dice: %77, H95: 9.79 mm
  • contact: Alireza Mehrtash, email: mehrtash at bwh.harvard.edu
  • Size: 6.4 GB


Command-line guide

docker pull deepinfer/wmh-segmenter-k2


docker run -t -v ~/data/wmh_test/:/data deepinfer/whm-segmenter-k2\
                   --ModelName wmh_segmenter\
                   --InputT1Volume /data/T1.nrrd\
                   --InputFLAIRVolume /data/flair.nrrd\
                   --OutputLabel /data/wmh_label.nrrd \


ModelName: ('wmh_segmenter')
InputT1Volume: (an existing filename locating the T1-Weighted MRI of the brain)
InputFLAIRVolume: (an existing filename locating the FLAIR MRI of the brain)
OutputLabel: (output path of the white matter hyperintensity (WMH) label)

verbose : 
verbose mode for printing additional details about the procedure.

Reuse and Citations

The WMH-Segmenter-K2 model is licensed under Slicer License.
For attribution in academic contexts, please cite the following work(s):

Article under review.

BibTeX citation

Article under review.