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.
@article{arxiv.1902.00550,
title = {2D and 3D Vascular Structures Enhancement via Multiscale Fractional Anisotropy Tensor},
author = {Haifa F. Alhasson and Shuaa S. Alharbi and Boguslaw Obara},
journal= {arXiv preprint arXiv:1902.00550},
year = {2019}
}