Researchers developed an automated tool that distinguishes arteries from veins in whole-brain images. It analyzes the shape and structure of vessel networks to classify them, achieving over 90% accuracy without relying on diameter measurements.
Most large-scale brain vascular datasets lack labels for arteries and veins. This gap blocks accurate blood flow simulations and cerebrovascular research. This tool allows scientists to quantify these networks across different imaging technologies, enabling better models for studying brain health.
✦ Automated labeling unlocks the full potential of existing brain imaging data.