Vessel Enhancement Based on Length-constrained Hessian Information

Vessel enhancement is an important pre-processing step of applications in vessel image analysis. However, most of the current methods are developed merely based on the intensity variety inside and outside vessel instead of considering the vessel path, which emphasizes the vascular structures via characterizing additional connectivity and length information. Aiming at further utilizing beneficial length information of vessels, we propose a novel method to impose length constraint on Hessian information for vessel enhancement. Specifically, Eigen analysis of multiscale Hessian matrix has been taken at each pixel for the local vesselness response and direction information. Then, vessel path is searched along each pixel's direction, as well as maintains the property of curvilinear smoothness. The proposed method is compared with three conventional vessel enhancement methods. The experiment results show that our proposed approach has the advantages of the fine response of low-contrast vessel region and less noise background. In addition, the quantity evaluation indicates that a state-of-art vessel enhancement performance could be achieved compared with other methods.