Non-linear Local Registration of Functional Data

Corouge, Isabelle; Barillot, Christian; Hellier, Pierre; Toulouse, P.; Gibaud, Bernard

doi:10.1007/3-540-45468-3_113

Cited by 7 publications

(10 citation statements)

References 14 publications

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“…inter-subject brain registration). Most work in this area has focused on brain registration, where there are a large number of publications [20, 21, 22, 27]. In addition, these types of methods have been applied to other single “organ” cases such as the heart and the prostate [23, 24, 29, 30].…”

Section: Introductionmentioning

confidence: 99%

A non-rigid registration method for serial lower extremity hybrid SPECT/CT imaging

Suh

Scheinost

Dione

et al. 2011

Medical Image Analysis

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Small animal X-ray computed tomographic (microCT) imaging of the lower extremities permits evaluation of arterial growth in models of hindlimb ischemia, and when applied serially can provide quantitative information about disease progression and aid in the evaluation of therapeutic interventions. The quantification of changes in tissue perfusion and concentration of molecular markers concurrently obtained using nuclear imaging requires the ability to non-rigidly register the microCT images over time, a task made more challenging by the potentially large changes in the positions of the legs due to articulation. While non-rigid registration methods have been extensively used in the evaluation of individual organs, application in whole body imaging has been limited, primarily because the scale of possible displacements and deformations is large resulting in poor convergence of most methods. In this paper we present a new method based on the extended demons algorithm that uses a level-set representation of the body contour and skeletal structure as an input. The proposed serial registration method reflects the natural physical moving combination of mouse anatomy in which the movement of bones is the framework for body movements, and the movement of skin constrains the detailed movements of the specific segmented body regions. We applied our method to both the registration of serial microCT mouse images and the quantification of microSPECT component of the serially hybrid microCT-SPECT images demonstrating improved performance as compared to existing registration techniques.

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Section: Introductionmentioning

confidence: 99%

A non-rigid registration method for serial lower extremity hybrid SPECT/CT imaging

Suh

Scheinost

Dione

et al. 2011

Medical Image Analysis

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“…First, most of the normal anatomical variability in the brain is in the cortical layered structure, and functional localization is extremely sensitive to the accuracy of registration in this area [192], [273], [274]. Second, the cortical surface structures, sulci and gyri, subdivide the brain into anatomically separate areas needed for activation labeling [275]- [277].…”

Section: Cortical Surface Registrationmentioning

confidence: 99%

Brain Functional Localization: A Survey of Image Registration Techniques

Gholipour

Kehtarnavaz

Briggs

et al. 2007

IEEE Trans. Med. Imaging

226

127

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Abstract-Functional localization is a concept which involves the application of a sequence of geometrical and statistical image processing operations in order to define the location of brain activity or to produce functional/parametric maps with respect to the brain structure or anatomy. Considering that functional brain images do not normally convey detailed structural information and, thus, do not present an anatomically specific localization of functional activity, various image registration techniques are introduced in the literature for the purpose of mapping functional activity into an anatomical image or a brain atlas. The problems addressed by these techniques differ depending on the application and the type of analysis, i.e., single-subject versus group analysis. Functional to anatomical brain image registration is the core part of functional localization in most applications and is accompanied by intersubject and subject-to-atlas registration for group analysis studies. Cortical surface registration and automatic brain labeling are some of the other tools towards establishing a fully automatic functional localization procedure. While several previous survey papers have reviewed and classified general-purpose medical image registration techniques, this paper provides an overview of brain functional localization along with a survey and classification of the image registration techniques related to this problem.Index Terms-Brain functional localization, fMRI image processing, functional imaging, survey of image registration techniques.

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“…Feature-based methods have been developed to overcome the limitations of gray-level methods (Collins et al, 1998;Corouge et al, 2001;Davatzikos, 1997). None of these methods, however, is able to handle large variations in sulcal anatomy, as well as irregular sulcal branching and discontinuity.…”

Section: Image Registration or Matchingmentioning

confidence: 99%

Geometric strategies for neuroanatomic analysis from MRI

et al. 2004

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In this paper, we describe ongoing work in the Image Processing and Analysis Group (IPAG) at Yale University specifically aimed at the analysis of structural information as represented within magnetic resonance images (MRI) of the human brain. Specifically, we will describe our applied mathematical approaches to the segmentation of cortical and subcortical structure, the analysis of white matter fiber tracks using diffusion tensor imaging (DTI), and the intersubject registration of neuroanatomical (aMRI) data sets. Many of our methods rally around the use of geometric constraints, statistical (MAP) estimation, and the use of level set evolution strategies. The analysis of gray matter structure and connecting white matter paths combined with the ability to bring all information into a common space via intersubject registration should provide us with a rich set of data to investigate structure and variation in the human brain in neuropsychiatric disorders, as well as provide a basis for current work in the development of integrated brain function-structure analysis.

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Non-linear Local Registration of Functional Data

Cited by 7 publications

References 14 publications

A non-rigid registration method for serial lower extremity hybrid SPECT/CT imaging

A non-rigid registration method for serial lower extremity hybrid SPECT/CT imaging

Brain Functional Localization: A Survey of Image Registration Techniques

Geometric strategies for neuroanatomic analysis from MRI

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