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The relationship between curvilinear structure enhancement and ridge detection methods

Lookup NU author(s): Dr Chris Willcocks, Professor Boguslaw ObaraORCiD

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This is the authors' accepted manuscript of an article that has been published in its final definitive form by Springer Nature, 2021.

For re-use rights please refer to the publisher's terms and conditions.


Abstract

© 2020, Springer-Verlag GmbH Germany, part of Springer Nature. Curvilinear structure detection and quantification is a large research area with many imaging applications in fields such as biology, medicine, and engineering. Curvilinear enhancement is often used as a pre-processing stage for ridge detection, but there has been little investigation into the relationship between enhancement and ridge detection. In this paper, we thoroughly evaluate the pair-wise combinations of different curvilinear enhancement and ridge detection methods across two highly varied datasets, as well as samples of three other datasets. In particular, we present the approaches complementing one another and the gained insights, which will aid researchers in designing generic ridge detectors.


Publication metadata

Author(s): Alhasson HF, Willcocks CG, Alharbi SS, Kasim A, Obara B

Publication type: Article

Publication status: Published

Journal: Visual Computer

Year: 2021

Volume: 37

Pages: 2263-2283

Print publication date: 01/08/2021

Online publication date: 22/10/2020

Acceptance date: 19/09/2020

Date deposited: 28/10/2021

ISSN (print): 0178-2789

ISSN (electronic): 1432-2315

Publisher: Springer Nature

URL: https://doi.org/10.1007/s00371-020-01985-4

DOI: 10.1007/s00371-020-01985-4


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