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Two and Three Dimensional Image Registration Based on B-Spline Composition and Level Sets

Part of: Physiological, cellular and medical topics Applications

Published online by Cambridge University Press:  07 February 2017

Chiu Ling Chan ,
Cosmin Anitescu ,
Yongjie Zhang  and
Timon Rabczuk
Chiu Ling Chan*
Affiliation:
Institute of Structural Mechanics, Bauhaus Universität Weimar, Germany
Cosmin Anitescu*
Affiliation:
Institute of Structural Mechanics, Bauhaus Universität Weimar, Germany
Yongjie Zhang*
Affiliation:
Department of Mechanical Engineering, Carnegie Mellon University, USA
Timon Rabczuk*
Affiliation:
Division of Computational Mechanics, Ton Duc Thang University, Ho Chi Minh City, Vietnam Faculty of Civil Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam Institute of Structural Mechanics, Bauhaus Universität Weimar, Germany
*
*Corresponding author.Email addresses:[email protected] (C. L. Chan), [email protected] (C. Anitescu), [email protected] (Y. Zhang), [email protected] (T. Rabczuk)
*Corresponding author.Email addresses:[email protected] (C. L. Chan), [email protected] (C. Anitescu), [email protected] (Y. Zhang), [email protected] (T. Rabczuk)
*Corresponding author.Email addresses:[email protected] (C. L. Chan), [email protected] (C. Anitescu), [email protected] (Y. Zhang), [email protected] (T. Rabczuk)
*Corresponding author.Email addresses:[email protected] (C. L. Chan), [email protected] (C. Anitescu), [email protected] (Y. Zhang), [email protected] (T. Rabczuk)
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Abstract

Amethod for non-rigid image registration that is suitable for large deformations is presented. Conventional registration methods embed the image in a B-spline object, and the image is evolved by deforming the B-spline object. In this work, we represent the image using B-spline and deform the image using a composition approach. We also derive a computationally efficient algorithm for calculating the B-spline coefficients and gradients of the image by adopting ideas from signal processing using image filters. We demonstrate the application of our method on several different types of 2D and 3D images and compare it with existing methods.

Keywords

Image registrationB-splinelevel setfree-form deformation

MSC classification

Secondary: 68U10: Image processing 92C55: Biomedical imaging and signal processing 62P10: Applications to biology and medical sciences
Type
Computational Software
Information
Communications in Computational Physics , Volume 21 , Issue 2 , February 2017 , pp. 600 - 622
Copyright
Copyright © Global-Science Press 2017 

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