Perivascular Space

Perivascular spaces (PVSs) are fluid-filled channels surrounding brain blood vessels, playing a crucial role in the brain's waste clearance system. Current research focuses on developing robust and generalizable automated methods, primarily using deep learning architectures like U-Net and nnU-Net, along with newer hybrid models combining convolutional neural networks and vision transformers, to accurately segment and quantify PVSs from MRI scans. This work aims to improve the efficiency and objectivity of PVS analysis, ultimately aiding in the diagnosis and understanding of age-related neurological diseases and vascular pathologies, particularly in regions like the basal ganglia. The development of reliable automated tools is critical for large-scale studies investigating the relationship between PVS morphology and clinical outcomes.