Foldover-free shape deformation for biomedicine

Authors: Yu, H., Zhang, J.J. and Lee, T.Y.

Editors: E.H. Shortliffe

http://www.journals.elsevier.com/journal-of-biomedical-informatics/

Journal: Journal of Biomedical Informatics

Volume: 48

Pages: 137-147

ISSN: 1532-0464

Shape deformation as a fundamental geometric operation underpins a wide range of applications, from geometric modelling, medical imaging to biomechanics. In medical imaging, for example, to quantify the difference between two corresponding images, 2D or 3D, one needs to find the deformation between both images. However, such deformations, particularly deforming complex volume datasets, are prone to the problem of foldover, i.e. during deformation, the required property of one-to-one mapping no longer holds for some points. Despite numerous research efforts, the construction of a mathematically robust foldover-free solution subject to positional constraints remains open. In this paper, we address this challenge by developing a radial basis function-based deformation method. In particular we formulate an effective iterative mechanism which ensures the foldover-free property is satisfied all the time. The experimental results suggest that the resulting deformations meet the internal positional constraints. In addition to radial basis functions, this iterative mechanism can also be incorporated into other deformation approaches, e.g. B-spline based FFDs, to develop different deformable approaches for various applications.

This source preferred by Hongchuan Yu

This data was imported from PubMed:

Authors: Yu, H., Zhang, J.J. and Lee, T.-Y.

Journal: J Biomed Inform

Volume: 48

Pages: 137-147

eISSN: 1532-0480

DOI: 10.1016/j.jbi.2013.12.011

Shape deformation as a fundamental geometric operation underpins a wide range of applications, from geometric modelling, medical imaging to biomechanics. In medical imaging, for example, to quantify the difference between two corresponding images, 2D or 3D, one needs to find the deformation between both images. However, such deformations, particularly deforming complex volume datasets, are prone to the problem of foldover, i.e. during deformation, the required property of one-to-one mapping no longer holds for some points. Despite numerous research efforts, the construction of a mathematically robust foldover-free solution subject to positional constraints remains open. In this paper, we address this challenge by developing a radial basis function-based deformation method. In particular we formulate an effective iterative mechanism which ensures the foldover-free property is satisfied all the time. The experimental results suggest that the resulting deformations meet the internal positional constraints. In addition to radial basis functions, this iterative mechanism can also be incorporated into other deformation approaches, e.g. B-spline based FFDs, to develop different deformable approaches for various applications.

This source preferred by Jian Jun Zhang

This data was imported from Scopus:

Authors: Yu, H., Zhang, J.J. and Lee, T.Y.

Journal: Journal of Biomedical Informatics

Volume: 48

Pages: 137-147

ISSN: 1532-0464

DOI: 10.1016/j.jbi.2013.12.011

Shape deformation as a fundamental geometric operation underpins a wide range of applications, from geometric modelling, medical imaging to biomechanics. In medical imaging, for example, to quantify the difference between two corresponding images, 2D or 3D, one needs to find the deformation between both images. However, such deformations, particularly deforming complex volume datasets, are prone to the problem of foldover, i.e. during deformation, the required property of one-to-one mapping no longer holds for some points. Despite numerous research efforts, the construction of a mathematically robust foldover-free solution subject to positional constraints remains open. In this paper, we address this challenge by developing a radial basis function-based deformation method. In particular we formulate an effective iterative mechanism which ensures the foldover-free property is satisfied all the time. The experimental results suggest that the resulting deformations meet the internal positional constraints. In addition to radial basis functions, this iterative mechanism can also be incorporated into other deformation approaches, e.g. B-spline based FFDs, to develop different deformable approaches for various applications. © 2013.

This source preferred by Jian Jun Zhang

This data was imported from Scopus:

Authors: Yu, H., Zhang, J.J. and Lee, T.-Y.

Journal: Journal of Biomedical Informatics

ISSN: 1532-0464

DOI: 10.1016/j.jbi.2013.12.011

Shape deformation as a fundamental geometric operation underpins a wide range of applications, from geometric modelling, medical imaging to biomechanics. In medical imaging, for example, to quantify the difference between two corresponding images, 2D or 3D, one needs to find the deformation between both images. However, such deformations, particularly deforming complex volume datasets, are prone to the problem of foldover, i.e. during deformation, the required property of one-to-one mapping no longer holds for some points. Despite numerous research efforts, the construction of a mathematically robust foldover-free solution subject to positional constraints remains open. In this paper, we address this challenge by developing a radial basis function-based deformation method. In particular we formulate an effective iterative mechanism which ensures the foldover-free property is satisfied all the time. The experimental results suggest that the resulting deformations meet the internal positional constraints. In addition to radial basis functions, this iterative mechanism can also be incorporated into other deformation approaches, e.g. B-spline based FFDs, to develop different deformable approaches for various applications. Crown Copyright © 2013.

This data was imported from Europe PubMed Central:

Authors: Yu, H., Zhang, J.J. and Lee, T.Y.

Journal: Journal of biomedical informatics

Volume: 48

Pages: 137-147

eISSN: 1532-0480

ISSN: 1532-0464

Shape deformation as a fundamental geometric operation underpins a wide range of applications, from geometric modelling, medical imaging to biomechanics. In medical imaging, for example, to quantify the difference between two corresponding images, 2D or 3D, one needs to find the deformation between both images. However, such deformations, particularly deforming complex volume datasets, are prone to the problem of foldover, i.e. during deformation, the required property of one-to-one mapping no longer holds for some points. Despite numerous research efforts, the construction of a mathematically robust foldover-free solution subject to positional constraints remains open. In this paper, we address this challenge by developing a radial basis function-based deformation method. In particular we formulate an effective iterative mechanism which ensures the foldover-free property is satisfied all the time. The experimental results suggest that the resulting deformations meet the internal positional constraints. In addition to radial basis functions, this iterative mechanism can also be incorporated into other deformation approaches, e.g. B-spline based FFDs, to develop different deformable approaches for various applications.

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