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2D and 3D vascular structures enhancement via multiscale fractional anisotropy tensor

Lookup NU author(s): Professor Boguslaw ObaraORCiD


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© Springer Nature Switzerland AG 2019. 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.

Publication metadata

Author(s): Alhasson HF, Alharbi SS, Obara B

Editor(s): Laura Leal-Taixé, Stefan Roth

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Computer Vision – ECCV 2018 Workshops

Year of Conference: 2018

Pages: 365-374

Online publication date: 23/01/2019

Acceptance date: 02/04/2018

ISSN: 0302-9743

Publisher: Springer Verlag


DOI: 10.1007/978-3-030-11024-6_26

Library holdings: Search Newcastle University Library for this item

Series Title: Lecture Notes in Computer Science

ISBN: 9783030110239