  Brain atrophy and white matter hyperintensity (WMH) are critical neuroimaging
features for ascertaining brain injury in cerebrovascular disease and multiple
sclerosis. Automated segmentation and quantification is desirable but existing
methods require high-resolution MRI with good signal-to-noise ratio (SNR). This
precludes application to clinical and low-field portable MRI (pMRI) scans, thus
hampering large-scale tracking of atrophy and WMH progression, especially in
underserved areas where pMRI has huge potential. Here we present a method that
segments white matter hyperintensity and 36 brain regions from scans of any
resolution and contrast (including pMRI) without retraining. We show results on
eight public datasets and on a private dataset with paired high- and low-field
scans (3T and 64mT), where we attain strong correlation between the WMH
($\rho$=.85) and hippocampal volumes (r=.89) estimated at both fields. Our
method is publicly available as part of FreeSurfer, at:
http://surfer.nmr.mgh.harvard.edu/fswiki/WMH-SynthSeg.
