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