BACKGROUND AND PURPOSE:
Midline shift (MLS) is an intracranial pathology characterized by the displacement of brain parenchyma across the skull’s midsagittal axis, typically caused by mass effect from space-occupying lesions or traumatic brain injuries. Prompt detection of MLS is crucial, because delays in identification and intervention can negatively impact patient outcomes. The gap we have addressed in this work is the development of a deep learning algorithm that encompasses the full s…