Construction of a statistical atlas of the whole heart from a large 4d ct database

[Show abstract] [Hide abstract] ABSTRACT: In this paper, we show how the concept of statistical deformation models (SDMs) can be used for the construction of average models of the anatomy and their variability. Tally erp 9 data recovery software SDMs are built by performing a statistical analysis of the deformations required to map anatomical features in one subject into the corresponding features in another subject. 7 databases in 7 weeks The concept of SDMs is similar to statistical shape models (SSMs) which capture statistical information about shapes across a population, but offers several advantages over SSMs.


3 database models First, SDMs can be constructed directly from images such as three-dimensional (3-D) magnetic resonance (MR) or computer tomography volumes without the need for segmentation which is usually a prerequisite for the construction of SSMs. Database programmer salary Instead, a nonrigid registration algorithm based on free-form deformations and normalized mutual information is used to compute the deformations required to establish dense correspondences between the reference subject and the subjects in the population class under investigation. Database developer salary Second, SDMs allow the construction of an atlas of the average anatomy as well as its variability across a population of subjects. Data recovery agent Finally, SDMs take the 3-D nature of the underlying anatomy into account by analysing dense 3-D deformation fields rather than only information about the surface shape of anatomical structures. Data recovery usb flash drive We show results for the construction of anatomical models of the brain from the MR images of 25 different subjects. Data recovery windows The correspondences obtained by the nonrigid registration are evaluated using anatomical landmark locations and show an average error of 1.40 mm at these anatomical landmark positions. Database definition We also demonstrate that SDMs can be constructed so as to minimize the bias toward the chosen reference subject.

[Show abstract] [Hide abstract] ABSTRACT: 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. Data recovery definition The method presented in this paper applies MI to measure the statistical dependence or information redundancy between the image intensities of corresponding voxels in both images, which is assumed to be maximal if the images are geometrically aligned. Database or database Maximization of MI is a very general and powerful criterion, because no assumptions are made regarding the nature of this dependence and no limiting constraints are imposed on the image content of the modalities involved. Data recovery software windows 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 solution, while robustness is evaluated with respect to implementation issues, such as interpolation and optimization, and image content, including partial overlap and image degradation. Cost of data recovery Our results demonstrate that subvoxel accuracy with respect to the stereotactic reference solution can be achieved completely automatically and without any prior segmentation, feature extraction, or other preprocessing steps which makes this method very well suited for clinical applications.

[Show abstract] [Hide abstract] ABSTRACT: In this paper the authors present a new approach for the nonrigid registration of contrast-enhanced breast MRI. Database first entity framework A hierarchical transformation model of the motion of the breast has been developed. Data recovery iphone 5 The global motion of the breast is modeled by an affine transformation while the local breast motion is described by a free-form deformation (FFD) based on B-splines. Raid 0 data recovery Normalized mutual information is used as a voxel-based similarity measure which is insensitive to intensity changes as a result of the contrast enhancement. 7 data recovery serial key Registration is achieved by minimizing a cost function, which represents a combination of the cost associated with the smoothness of the transformation and the cost associated with the image similarity. Database modeling The algorithm has been applied to the fully automated registration of three-dimensional (3-D) breast MRI in volunteers and patients. A database record is an entry that contains In particular, the authors have compared the results of the proposed nonrigid registration algorithm to those obtained using rigid and affine registration techniques. Java database The results clearly indicate that the nonrigid registration algorithm is much better able to recover the motion and deformation of the breast than rigid or affine registration algorithms.

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