bigrbrain - WMH Segmentation Challenge
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WMH Segmentation Challenge

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    • Manual reference standard
    • MRI parameters
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    • Teams:
    • achilles
    • acunet
    • arg
    • bigrbrain
    • bigrbrain 2
    • bioengineering_espol_team
    • buckeye_ai
    • caai_amh
    • cian
    • coroflo
    • dice
    • fmrib-truenet
    • fmrib-truenet 2
    • hadi
    • himinn
    • ipmi-bern
    • k2
    • knight
    • livia
    • lrde
    • misp
    • misp 2
    • neuro.ml
    • neuro.ml 2
    • nic-vicorob
    • nih_cidi
    • nih_cidi 2
    • nist
    • nlp_logix
    • pitt-vamp
    • pitt-vamp 2
    • pgs
    • rasha_simple
    • rasha_improved
    • scan
    • skkumedneuro
    • sysu_media
    • sysu_media 2
    • text_class
    • tig
    • tig 2
    • tignet
    • tum_ibbm
    • uned
    • uned 2
    • uned_contrast
    • upc_dlmi
    • wta
    • wta 2
  • Organizers
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bigrbrain

A convolutional neural network with a 3D U-Net architecture, followed by a posterior-CRF to improve the results of the CNN.

Description of the method.
Docker container of this method.

An update of this method is available: bigrbrain 2.

by Hugo J. Kuijf, Image Sciences Institute, UMC Utrecht, the Netherlands

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