  The detection of vascular structures from noisy images is a fundamental
process for extracting meaningful information in many applications. Most
well-known vascular enhancing techniques often rely on Hessian-based filters.
This paper investigates the feasibility and deficiencies of detecting
curve-like structures using a Hessian matrix. The main contribution is a novel
enhancement function, which overcomes the deficiencies of established methods.
Our approach has been evaluated quantitatively and qualitatively using
synthetic examples and a wide range of real 2D and 3D biomedical images.
Compared with other existing approaches, the experimental results prove that
our proposed approach achieves high-quality curvilinear structure enhancement.
