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.

翻译：脑萎缩和白质高信号（WMH）是评估脑血管疾病和多发性硬化症脑损伤的关键神经影像学特征。自动分割与量化方法虽备受期待，但现有技术依赖具有良好信噪比（SNR）的高分辨率MRI，因此难以应用于临床及低场便携式MRI（pMRI）扫描，从而阻碍了脑萎缩与WMH进展的大规模追踪——尤其是在低场pMRI潜力巨大的医疗资源匮乏地区。本文提出一种无需重新训练即可从任意分辨率和对比度（包括pMRI）的扫描中分割白质高信号及36个脑区的方法。我们在八个公开数据集及一个包含配对高场（3T）与低场（64mT）扫描的私有数据集上验证结果，发现两场估测的WMH体积（ρ=0.85）与海马体积（r=0.89）高度相关。该方法已作为FreeSurfer的组成部分公开发布，网址为：http://surfer.nmr.mgh.harvard.edu/fswiki/WMH-SynthSeg。