Yu Bo
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An Efficient Numerical Method for Mean Curvature-Based Image Registration Model
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Indexed by:期刊论文

Date of Publication:2017-02-01

Journal:EAST ASIAN JOURNAL ON APPLIED MATHEMATICS

Included Journals:SCIE

Volume:7

Issue:1

Page Number:125-142

ISSN No.:2079-7362

Key Words:Deformable image registration; regularization; multilevel; mean curvature

Abstract:Mean curvature-based image registration model firstly proposed by ChumchobChen- Brito (2011) offered a better regularizer technique for both smooth and nonsmooth deformation fields. However, it is extremely challenging to solve efficiently this model and the existing methods are slow or become efficient only with strong assumptions on the smoothing parameter (SS). In this paper, we take a different solution approach. Firstly, we discretize the joint energy functional, following an idea of relaxed fixed point is implemented and combine with Gauss-Newton scheme with Armijo's Linear Search for solving the discretized mean curvature model and further to combine with a multilevel method to achieve fast convergence. Numerical experiments not only confirm that our proposed method is efficient and stable, but also it can give more satisfying registration results according to image quality.

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Gender:Male

Alma Mater:吉林大学

Degree:Doctoral Degree

School/Department:数学科学学院

Discipline:Computational Mathematics. Financial Mathematics and Actuarial Science

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