2D and 3D Vascular Structures Enhancement via Multiscale Fractional Anisotropy Tensor

Haifa F. Alhasson, Shuaa S. Alharbi, Boguslaw Obara; Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 2018, pp. 0-0

Abstract


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.

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[bibtex]
@InProceedings{Alhasson_2018_ECCV_Workshops,
author = {Alhasson, Haifa F. and Alharbi, Shuaa S. and Obara, Boguslaw},
title = {2D and 3D Vascular Structures Enhancement via Multiscale Fractional Anisotropy Tensor},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV) Workshops},
month = {September},
year = {2018}
}