Automated Dentate Nucleus Segmentation from QSM Images Using Deep Learning.

A preprint abstract from medrxiv.org discusses the development of a dentate nucleus (DN) segmentation tool using deep learning (DL) applied to brain quantitative susceptibility mapping (QSM) images. The study collected brain QSM images from healthy controls and individuals with cerebellar ataxia or multiple sclerosis. The researchers implemented a two-step approach, consisting of a localization model followed by DN segmentation, and achieved promising results. The model demonstrated generalizability across different datasets and can be used for biomarker discovery in observational, natural history, and treatment trials. However, it is important to note that this preprint has not yet undergone peer review. [Extracted from the article]