3D Vessel Segmentation

3D vessel segmentation aims to automatically identify and delineate blood vessels within three-dimensional medical images, facilitating improved diagnosis and treatment planning. Current research emphasizes developing efficient and accurate segmentation methods, often employing deep learning architectures like U-Net variations and transformers, while also exploring weakly-supervised or semi-supervised approaches to reduce the need for extensive manual annotations. These advancements are crucial for various applications, including computer-aided diagnosis of vascular diseases and image-guided interventions, ultimately improving patient care and accelerating medical research.