Vessel Detection

Vessel detection encompasses the automated identification and segmentation of vessels in various imaging modalities, aiming to improve diagnostic accuracy and efficiency across diverse applications. Current research emphasizes improving the robustness of detection, particularly for small or poorly defined vessels, utilizing deep learning architectures like U-Nets, transformers, and YOLO variants, often coupled with advanced preprocessing techniques and data augmentation strategies. These advancements have significant implications for medical imaging (e.g., improved diagnosis of cardiovascular and retinal diseases), maritime surveillance (e.g., enhanced tracking and monitoring of vessels), and other fields requiring precise and efficient vessel analysis.