wmh_seg: Transformer based U-Net for Robust and Automatic White Matter Hyperintensity Segmentation across 1.5T, 3T and 7T

arXiv:2402.12701v1 Announce Type: cross
Abstract: White matter hyperintensity (WMH) remains the top imaging biomarker for neurodegenerative diseases. Robust and accurate segmentation of WMH holds paramount significance for neuroimaging studies. The growing shift from 3T to 7T MRI necessitates robust tools for harmonized segmentation across field strengths and artifacts. Recent deep learning models exhibit promise in WMH segmentation but still face challenges, including diverse training data representation and limited analysis of MRI artifacts' impact. To address these, we introduce wmh_seg, a …

abstract arxiv cs.cv diseases eess.iv imaging matter mri neuroimaging robust segmentation shift significance studies tools transformer type