Dual energy CT and deep learning for an automated volumetric segmentation of the major intracranial tissues : Feasibility and initial findings
Background: Magnetic resonance imaging (MRI) has traditionally been preferred over computed tomography (CT) for segmentation of intracranial structures due to its superior low contrast resolution. However, a reliable CT-based segmentation could improve patient management when MRI is not practical. Despite advancements in CT imaging, such as enhanced tissue differentiation using virtual monoenerget
