Vessel Structure

Vessel structure analysis focuses on accurately identifying, segmenting, and characterizing vessel-like structures across diverse applications, from medical imaging to wood science. Current research heavily utilizes deep learning, employing architectures like U-Nets, YOLOv8, and recurrent encoder-decoder networks, often incorporating techniques such as transfer learning, graph clustering, and geodesic methods to improve segmentation accuracy and address challenges like incomplete or fragmented structures. These advancements enable more precise and efficient analysis of vessel networks in various contexts, leading to improved diagnostic tools in medicine, enhanced material characterization in forestry, and more robust autonomous navigation systems.