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On Combining Algorithms for Deformable Image Registration
2012We propose a meta-algorithm for registration improvement by combining deformable image registrations (MetaReg). It is inspired by a well-established method from machine learning, the combination of classifiers. MetaReg consists of two main components: (1) A strategy for composing an improved registration by combining deformation fields from different ...
Sascha E. A. Muenzing +2 more
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Deformable image registration based on elastodynamics
Machine Vision and Applications, 2015This paper presents a novel method for 2D inter-subject non-rigid image registration. It is motivated by the ideas derived from elastodynamics which is the subclass of linear elastic theory. We propose to model the non-rigid deformations as elastic waves which are characterized by elastodynamics wave equation. Our registration method is formulated in a
Sahar Ahmad, Muhammad Faisal Khan
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An algebraic framework for deformable image registration
2016 23rd International Conference on Pattern Recognition (ICPR), 2016This paper presents a novel approach to deformable image registration using a parametric transformation model. The aligning transformation is simply found by solving a system of non-linear equations. Each equation is generated by integrating the product of a set of polynomial functions and the image intensity function over corresponding image domains ...
Zsolt Sánta, Zoltan Kato
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Mid-space-independent deformable image registration [PDF]
NeuroImage, 2017 Aligning images in a mid-space is a common approach to ensuring that deformable image registration is symmetric - that it does not depend on the arbitrary ordering of the input images. The results are, however, generally dependent on the mathematical definition of the mid-space.
Iman Aganj +2 more
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Local statistical deformation models for deformable image registration
Neurocomputing, 2018Abstract A fast and robust image registration algorithm for high-dimensional brain Magnetic Resonance images was developed based on the statistical deformation models (SDMs). This model learns deformation fields and achieves fast and robust registration by greatly reducing transformation dimensionality.
Songyuan Tang +6 more
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Registration of local deformations in images
2008 Second International Conference on Electrical Engineering, 2008This paper proposes a radial basis function(RBF) with finite support to register non rigid local deformations present in a image pair. The criteria to evaluate accuracy of local transformation function is also proposed. Results of proposed RBF are analyzed and compared with the existing RBFs, based on the evaluation criteria and similarity measures ...
Adil Masood Siddiqui, Muhammad Saleem
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Sliding Geometries in Deformable Image Registration
2012Regularization is used in deformable image registration to encourage plausible displacement fields, and significantly impacts the derived correspondences. Sliding motion, such as that between the lungs and chest wall and between the abdominal organs, complicates registration because many regularizations are global smoothness constraints that produce ...
Danielle F. Pace +2 more
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DIRBoost: An algorithm for boosting deformable image registration
2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), 2012We introduce a novel boosting algorithm to boost - i.e. improve on - existing methods for deformable image registration. The proposed DIRBoost algorithm is inspired by the theory on hypothesis boosting, well-known in the field of machine learning. DIRBoost involves a classifier for landmark-based Registration Error Detection (RED).
Sascha E. A. Muenzing +2 more
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Image registration with local deformation
IEEE APCCAS 2000. 2000 IEEE Asia-Pacific Conference on Circuits and Systems. Electronic Communication Systems. (Cat. No.00EX394), 2002This research is focused on the study of local-type image registration techniques, which concern the establishment of transform mapping between pixels of two correlated images with local deformation. The proposed algorithm is actually hybrid that locally dynamic corrective matching and global surface-spline fitting techniques are combined.
null Wen-Nung Lie +2 more
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Deformable registration of male pelvises in CT images
2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (IEEE Cat No. 04EX821), 2005In this paper, a method for deformable registration of male pelvises in CT images is proposed. It is composed of three major steps. Firstly, an attribute vector is defined for each voxel in the image, and is used to reflect the density distribution of the bone tissues in the neighborhood of that voxel. Different anatomical structures thus own different
Yiqiang Zhan +2 more
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