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Contrast-independent curvilinear structure enhancement in 3D biomedical images

Lookup NU author(s): Professor Boguslaw Obara

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This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by IEEE, 2017.

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Abstract

© 2017 IEEE. A wide range of biomedical applications require detection, quantification and modelling of curvilinear structures in 3D images. Here we propose a 3D contrast-independent approach to enhance curvilinear structures based on the 3D Phase Congruency Tensor concept. The results show that the proposed method is insensitive to intensity variations along the 3D curve, and provides successful enhancement within noisy regions. The quality of the 3D Phase Congruency Tensor is evaluated by comparing it with state-of-the-art intensity-based approaches on both synthetic and real biological images.


Publication metadata

Author(s): Sazak C, Obara B

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 14th International Symposium on Biomedical Imaging (ISBI 2017)

Year of Conference: 2017

Pages: 1165-1168

Online publication date: 19/06/2017

Acceptance date: 02/04/2016

Date deposited: 04/05/2021

ISSN: 1945-8452

Publisher: IEEE

URL: https://doi.org/10.1109/ISBI.2017.7950723

DOI: 10.1109/ISBI.2017.7950723

Library holdings: Search Newcastle University Library for this item

ISBN: 9781509011728


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