This module is currently only available in the development version of FreeSurfer

Author: Pablo Laso

E-mail: plaso [at] kth.se

Rather than directly contacting the author, please post your questions on this module to the FreeSurfer mailing list at freesurfer [at] nmr.mgh.harvard.edu

If you use WMH-SynthSeg in your analysis, please cite:


  1. General Description
  2. Usage
  3. Frequently asked questions (FAQ)

1. General Description

This tool is a version of SynthSeg that, in addition to segmeting anatomy, also provides segmentations for white matter hyperintensity (WMH) - or hypointensities, in T1-like modalities. As the original SynthSeg, WMH-SynthSeg works out of the box and can handle brain MRI scans of any contrast and resolution. Unlike SynthSeg, WMH-SynthSeg is designed to adapt to low-field MRI scans with low resolution and signal-to-noise ratio (which makes it potentially a bit less accurate on high-resolution data acquired at high field).

As for SynthSeg, the output segmentations are returned at high resolution (1mm isotropic), regardless of the resolution of the input scans. The code can run on the GPU (3s per scan) as well as the CPU (1 minute per scan). The list of segmented structures is the same as for SynthSeg 2.0 (plus the WMH label, which is FreeSurfer label 77). Below are some examples of segmentations given by WMH-SynthSeg.


2. Usage

You can use WMH-SynthSeg with the following command:

mri_WMHsynthseg --i <input> --o <output> [--csv_vols <CSV file>] [--device <device>]  [--threads <threads>] [--crop] [--save_lesion_probabilities]


Important: If you wish to process several scans, we highly recommend that you put them in a single folder, rather than calling mri_WMHsynthseg individually on each scan. This will save the time required to set up the software for each scan.

3. Frequently asked questions (FAQ)

About 32GB of RAM memory.

No! Because we applied aggressive augmentation during training (see paper), this tool is able to segment both processed and unprocessed data. So there is no need to apply bias field correction, skull stripping, or intensity normalization.

This is because the volumes are computed upon a soft segmentation, rather than the discrete segmentation. The same happens with the main recon-all stream: if you compute volumes by counting voxels in aseg.mgz, you don't get the values reported in aseg.stats.

This tool can be run on Nifti (.nii/.nii.gz) and FreeSurfer (.mgz) scans.

If you have a multi-core machine, you can increase the number of threads with the --threads flag (up to the number of cores).

Simply because, in order to output segmentations at 1mm resolution, the network needs the input images to be at this particular resolution! We highlight that the resampling is performed internally to avoid the dependence on any external tool.

This may happens with viewers other than FreeSurfer's Freeview, if they do not handle headers properly. We recommend using Freeview but, if you want to use another viewer, you may can use mri_convert with the -rl flag to obtain resampled images, which any other view will display correctly. Something like: 'mri_convert input.nii.gz input.resampled.nii.gz -rl segmentation.nii.gz'.

WMH-SynthSeg (last edited 2024-06-28 16:14:38 by JuanIglesias)