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Nonrigid Brain MR Image Registration Using Uniform Spherical Region Descriptor
"... Abstract—There are two main issues that make nonrigid image registration a challenging task. First, voxel intensity similarity may not be necessarily equivalent to anatomical similarity in the image correspondence searching process. Second, during the imaging process, some interferences such as unex ..."
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Cited by 5 (1 self)
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Abstract—There are two main issues that make nonrigid image registration a challenging task. First, voxel intensity similarity may not be necessarily equivalent to anatomical similarity in the image correspondence searching process. Second, during the imaging process, some interferences
Joint Learning of Appearance and Transformation for Predicting Brain MR Image Registration
"... Abstract. We propose a new approach to register the subject image with the template by leveraging a set of training images that are pre-aligned to the template. We argue that, if voxels in the subject and the training images share similar local appearances and transformations, they may have common c ..."
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Cited by 1 (0 self)
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. In the final, we efficiently refine our estimated transformation field via existing registration method. We apply our method to registering brain MR images, and conclude that the proposed method is competent to improve registration performances in terms of time cost as well as accuracy. 1
Feature based nonrigid brain MR image registration with symmetric alpha stable filters
- IEEE Trans. on Med. Img
, 2010
"... Abstract—A new feature based nonrigid image registration method for magnetic resonance (MR) brain images is presented in this paper. Each image voxel is represented by a rotation invariant feature vector, which is computed by passing the input image volumes through a new bank of symmetric alpha stab ..."
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Cited by 7 (2 self)
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Abstract—A new feature based nonrigid image registration method for magnetic resonance (MR) brain images is presented in this paper. Each image voxel is represented by a rotation invariant feature vector, which is computed by passing the input image volumes through a new bank of symmetric alpha
A new coarse-to-fine framework for 3D brain MR image registration, in
- of Lecture Notes in Computer Science
, 2005
"... Abstract. Registration, that is, the alignment of multiple images, has been one of the most challenging problems in the field of computer vision. It also serves as an important role in biomedical image analysis and its applications. Although various methods have been proposed for solving different k ..."
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Cited by 5 (5 self)
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kinds of registration problems in computer vision, the results are still far from ideal when it comes to real world biomedical image applications. For instance, in order to register 3D brain MR images, current state of the art registration methods use a multiresolution coarse-to-fine algorithm, which
Nonrigid registration using free-form deformations: Application to breast MR images
- IEEE Transactions on Medical Imaging
, 1999
"... Abstract — In this paper we present a new approach for the nonrigid registration of contrast-enhanced breast MRI. A hierarchical transformation model of the motion of the breast has been developed. The global motion of the breast is modeled by an affine transformation while the local breast motion i ..."
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Cited by 697 (36 self)
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of the cost associated with the smoothness of the transformation and the cost associated with the image similarity. The algorithm has been applied to the fully automated registration of three-dimensional (3-D) breast MRI in volunteers and patients. In particular, we have compared the results of the proposed
Multimodality Image Registration by Maximization of Mutual Information
- IEEE TRANSACTIONS ON MEDICAL IMAGING
, 1997
"... A new approach to the problem of multimodality medical image registration is proposed, using a basic concept from information theory, mutual information (MI), or relative entropy, as a new matching criterion. The method presented in this paper applies MI to measure the statistical dependence or in ..."
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Cited by 791 (10 self)
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and no limiting constraints are imposed on the image content of the modalities involved. The accuracy of the MI criterion is validated for rigid body registration of computed tomography (CT), magnetic resonance (MR), and photon emission tomography (PET) images by comparison with the stereotactic registration
Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm
- IEEE TRANSACTIONS ON MEDICAL. IMAGING
, 2001
"... The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogram-based model, the FM has an intrinsic limi ..."
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Cited by 639 (15 self)
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The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogram-based model, the FM has an intrinsic
Sparse MRI: The Application of Compressed Sensing for Rapid MR Imaging
- MAGNETIC RESONANCE IN MEDICINE 58:1182–1195
, 2007
"... The sparsity which is implicit in MR images is exploited to significantly undersample k-space. Some MR images such as angiograms are already sparse in the pixel representation; other, more complicated images have a sparse representation in some transform domain–for example, in terms of spatial finit ..."
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Cited by 538 (11 self)
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The sparsity which is implicit in MR images is exploited to significantly undersample k-space. Some MR images such as angiograms are already sparse in the pixel representation; other, more complicated images have a sparse representation in some transform domain–for example, in terms of spatial
Multi-Modal Volume Registration by Maximization of Mutual Information
, 1996
"... A new information-theoretic approach is presented for finding the registration of volumetric medical images of differing modalities. Registration is achieved by adjustment of the relative pose until the mutual information between images is maximized. In our derivation of the registration procedure, ..."
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Cited by 458 (23 self)
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A new information-theoretic approach is presented for finding the registration of volumetric medical images of differing modalities. Registration is achieved by adjustment of the relative pose until the mutual information between images is maximized. In our derivation of the registration procedure
A NOVEL MULTI-LAYER FRAMEWORK FOR NON-RIGID IMAGE REGISTRATION
"... Brain magnetic resonance (MR) images consist of different structures and features when they are observed at different scales and layers. Conventional non-rigid brain MR image registration methods mainly estimate the optimum transformation by relying on the information of a single layer and this can ..."
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Cited by 1 (0 self)
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Brain magnetic resonance (MR) images consist of different structures and features when they are observed at different scales and layers. Conventional non-rigid brain MR image registration methods mainly estimate the optimum transformation by relying on the information of a single layer and this can
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