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2012
DOI: 10.1007/978-3-642-27579-1_32
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Development of an Accurate Method for Motion Analyses of the Heart Wall Based on Medical Imagery

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Cited by 4 publications
(4 citation statements)
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“…There are many references that deal with the role of registration and its applications in medical image processing, for an overview, see [29,27,23,12]. Moreover, specific applications to medical image registration involving Magnetic Resonance Imaging (MRI) and Computer Tomography (CT) are considered in [23,12,31,30]. Registration is also one of the basic stages of image fusion, which is the process of combining multiple information from a set of images.…”
Section: Introductionmentioning
confidence: 99%
“…There are many references that deal with the role of registration and its applications in medical image processing, for an overview, see [29,27,23,12]. Moreover, specific applications to medical image registration involving Magnetic Resonance Imaging (MRI) and Computer Tomography (CT) are considered in [23,12,31,30]. Registration is also one of the basic stages of image fusion, which is the process of combining multiple information from a set of images.…”
Section: Introductionmentioning
confidence: 99%
“…A number of authors have investigated the most popular radial basis function transformations in the image registration context: thin plate spline [7,31], multiquadric [30,41], inverse multiquadric [41], and Gaussian transformations [7]. A more specific application which involves registration and includes imaging techniques, such as computer tomography and magnetic resonance imaging, can be found in [37,38]. Since using globally supported RBFs, as for example the Gaussians, a single landmark pair change may influence the whole registration result, in the last two decades several methods have been presented to circumvent this disadvantage, such as weighted least squares and weighted mean methods (WLSM and WMM, respectively) [24], compactly supported radial basis functions (CSRBFs), especially Wendland's and Gneiting's functions [14,15,23], and elastic body splines (EBSs) [29].…”
Section: Introductionmentioning
confidence: 99%
“…The landmark-based registration problem can be formulated in the context of multivariate scattered data interpolation, and solved by different techniques, among which radial basis functions (RBFs) play a preminent role (see, e.g., [7,24]). The use of RBF transformations, in particular of the thin plate splines, for point-based image registration was first proposed by Bookstein [3], and it is still common (see [20,21] and the software package MIPAV [16]). …”
Section: Introductionmentioning
confidence: 99%