3D Vessel

3D vessel reconstruction aims to create accurate three-dimensional models of blood vessels from two-dimensional medical images, primarily to improve diagnosis and treatment planning for vascular diseases. Current research focuses on improving the accuracy and efficiency of reconstruction using deep learning techniques, such as graph convolutional networks and U-Net architectures, often incorporating strategies to handle sparse data and complex vessel morphologies. These advancements are driven by the need to reduce radiation exposure in procedures like angiography and to enable more precise, automated interventions in fields like robotic surgery and image-guided therapy.