A Multi-Cohort nnU-Net for White Matter Hyperintensity Segmentation Across 2D and 3D FLAIR Acquisitions

Background White matter hyperintensities (WMH) are increasingly pooled across aging, cerebral small vessel disease (CSVD), and dementia cohorts that differ in both disease composition and FLAIR acquisition. Most automated segmentation tools were developed within a narrower range of populations or protocols, and few have been tested for whether segmentation accuracy and error remain consistent across conventional 2D and isotropic 3D FLAIR, or whether the choice of algorithm alters downstream clinical associations. Methods We developed a single nnU-Net model, taking FLAIR and T1-weighted images

This content is for informational purposes only and is not medical advice. It is not intended to diagnose, treat, cure, or prevent any disease. Consult a healthcare professional before starting any supplement, treatment, or program: especially if you are pregnant, nursing, taking medication, or managing a health condition.