Automated Midline Shift Detection in Head CT Using Localization and Symmetry Techniques Based on User-Selected Slice

We developed an AI model that reliably identifies the lateral ventricles and the cerebral midline across various pathologies in patient CT scans. Most importantly, our model accurately identifies and stratifies clinically significant and emergent MLS from nonemergent cases. This could serve as a foundational element for a future clinically integrated approach that flags urgent studies for expedited review, potentially facilitating more timely treatment when necessary.