Curvilinear Structure

Curvilinear structure segmentation focuses on accurately identifying and delineating elongated, curved objects within images, a crucial task across diverse fields like medical imaging and infrastructure inspection. Current research emphasizes developing robust deep learning models, often incorporating novel architectures like U-Nets and CycleGANs, to address challenges posed by variations in object appearance, low contrast, and complex backgrounds. These advancements improve the accuracy and generalizability of segmentation, leading to more reliable analysis in applications ranging from diagnosing vascular diseases to assessing road conditions.