An improved model for joint segmentation and registration based on linear curvature smoother

Ibrahim, Mazlinda, Chen, Ke ORCID: 0000-0002-6093-6623 and Rada, Lavdie (2016) An improved model for joint segmentation and registration based on linear curvature smoother. JOURNAL OF ALGORITHMS & COMPUTATIONAL TECHNOLOGY, 10 (4). pp. 314-324.

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Abstract

<jats:p>Image segmentation and registration are two of the most challenging tasks in medical imaging. They are closely related because both tasks are often required simultaneously. In this article, we present an improved variational model for a joint segmentation and registration based on active contour without edges and the linear curvature model. The proposed model allows large deformation to occur by solving in this way the difficulties other jointly performed segmentation and registration models have in case of encountering multiple objects into an image or their highly dependence on the initialisation or the need for a pre-registration step, which has an impact on the segmentation results. Through different numerical results, we show that the proposed model gives correct registration results when there are different features inside the object to be segmented or features that have clear boundaries but without fine details in which the old model would not be able to cope.</jats:p>

Item Type:	Article
Uncontrolled Keywords:	Image registration, non-parametric image registration, interactive segmentation, variational models
Depositing User:	Symplectic Admin
Date Deposited:	06 Oct 2016 13:55
Last Modified:	21 Aug 2023 09:21
DOI:	10.1177/1748301816668027
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3003634