A. Amini, R. Owen, L. Staib, P. Anandan, and J. Duncan. non-rigid motion models for tracking the left ventricular wall. Lecture notes in computer science: Information processing in medical images. 1991. Springer-Verlag.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....studied by medical image processing groups. Since its creation in 1989, our group has pioneered work in the use of deformable models to extract the left ventricle [5, 17, 6, 8, 19, 16, 7, 13] Other groups have also contributed to the understanding of the complex deformation of the ventricle [4, 31, 3, 30, 36, 29]. Over the last decade, many surface reconstruction problems have been formulated as the minimization of an energy functional corresponding to a model of the surface. Using deformable models and templates, the extraction of a shape is obtained through minimization of an energy composed of an ....

A. Amini, R. Owen, P. Anandan, and J. Duncan. Non-rigid motion models for tracking the left ventricular wall. In Information processing in medical images, Lecture notes in computer science, pages 343357, 1991. Springer-Verlag.

....studied by medical image processing groups. Since its creation in 1989, our group has pioneered work in the use of deformable models to extract the left ventricle [5, 17, 6, 8, 19, 16, 7, 13] Other groups have also contributed to the understanding of the complex deformation of the ventricle [4, 31, 3, 30, 36, 29]. Over the last decade, many surface reconstruction problems have been formulated as the minimization of an energy functional corresponding to a model of the surface. Using deformable models and templates, the extraction of a shape is obtained through minimization of an energy composed of an ....

A. Amini, R. Owen, P. Anandan, and J. Duncan. Non-rigid motion models for tracking the left ventricular wall. In Information processing in medical images, Lecture notes in computer science, pages 343357, 1991. Springer-Verlag.

....the model depends only on the boundary, a curve in our 2D solution space. This model is different from the one explored previously [2] whichinvolved a description that provided full 2D versatility. Flexible 1D curves in a 2D space maybe thought of as splines, manifolds in differential geometry [3], or snakes [4] The flexible curvemaybeinterpreted in terms of an analogous physical system, a closed loop of elastic material that undergoes distortion while being constrained to lie in the plane. Then the constraints placed on the curve correspond to the properties of the material being ....

A. A. Amini, R. L. Owen, P. Anandan, and J. S. Duncan. Non-rigid motion models for tracking the left-ventricular wall. In A. C. F. Colchester and D. Hawkes, editors, Info. Processing in Med. Imag., pages 343--357. Springer-Verlag, 1991.

....and modality invariant features compared to intensity properties. The input correspondences of boundary structures can be obtained by using, for example, active surface models [12] 27] or alternatively by applying boundary matching algorithms such as, for example, curvature based methods [1], 18] In this paper, however, we do not attempt to discuss in detail the concrete methods which could be applied for de nition of the required boundary mapping. 2.8 Numerical solution After discretization, we obtain the displacement eld for deformation from a system of linear equations. Due ....

A.A. Amini, R.L. Owen, P. Anandan, and J.S. Duncan. Non-rigid motion models for tracking the left-ventricular wall. In Lecture Note in Computer Science: Information Processing in Medical Images, pages 343-356. Springer-Verlag, 1991.

....deformable models [10] physically based modelling for nonrigid motion analysis has become extremely popular. Terzopoulos et al. use a dynamic deformable model to infer the 3D structure of nonrigid objects [23, 11] Duncan et. al use bending energy and surface curvature to analyze nonrigid motion [1] (an alternative formulation can be found in [3] In [13] nonrigid motion is assumed to be locally conformal, while Chen and Huang use a tensor based analysis to estimate global motion parameters and local deformation [6] Superquadrics [20] have shown to be useful predefined shapes globally and ....

A. Amini, R. Owen, L. Staib, P. Anandan, and J. Duncan. Non-rigid motion models for tracking the left ventricular wall. Lecture notes in computer science: Information processing in medical images. Springer-Verlag, 1991.

....Partial equations are used to determine the dynamics of the blood within the boundary conditions of the vessel. In addition to utilising these techniques in simulating deformable objects and segmenting static structures, deformable models have been used to track dynamic structures. For instance, [22] tracked the motion of the left ventricle of the heart to diagnose heart diseases. He utilised curves and surfaces as basic elements of the deformable model and used differential geometry to calculate the internal energy in the model. 6.6 WebSTer s physically based model: Design Now that we have ....

A. Amini, R. Owen, and et. al. Non-rigid motion models for tracking the left ventricular wall. In A.C. Colchester and D.J. Hawkes, editors, Lecture Notes in Computer Science: (Vol 511) Information Processing in Medical Imaging, pages 343--57. Spring- Verlag, 1991.

....of global object models have been proposed for recognition tasks but these are unsuited to the atlas problem because they cannot describe local changes in shape. Even the hybrid schemes [7, 8, 9] which combine lumped and distributed parameter models, and many of the distributed parameter models [10, 11] are generally not appropriate because only the surface or contour of an object is modeled, whereas fully volumetric representations are the most useful for the atlas problem. In the present paper, we present a Bayesian decision theoretic formulation of the volumetric image matching problem. The ....

Amini AA, Owen RL, Anandan P, Duncan JS. Non-rigid motion models for tracking the left ventricular wall. In: Colchester ACF, Hawkes DJ, eds. Information Processing in Medical Imaging. Berlin:Springer-Verlag, 1991;LNCS 511:343--357.

....studied by medical image processing groups. Since its creation in 1989, our group has pioneered work in the use of deformable models to extract the left ventricle [5, 17, 6, 8, 19, 16, 7, 13] Other groups have also contributed to the understanding of the complex deformation of the ventricle [4, 31, 3, 30, 36, 29]. Over the last decade, many surface reconstruction problems have been formulated as the minimization of an energy functional corresponding to a model of the surface. Using deformable models and templates, the extraction of a shape is obtained through minimization of an energy composed of an ....

A. Amini, R. Owen, P. Anandan, and J. Duncan. Non-rigid motion models for tracking the left ventricular wall. In Information processing in medical images, Lecture notes in computer science, pages 343357, 1991. Springer-Verlag.

....are reported to be stable and robust approach for 2 D and 3 D segmentation. Alternatively to using deformable models, one can also extract object boundaries in both the source and target image and then use some matching techniques, e.g. the minimal distance algorithm [3] or curvature based methods [1], 26] The advantage of such explicit segmentation is that we directly work with boundaries of the objects and not with their approximations obtained by using deformable models. The main drawback is, of course, that segmentation of real brain images is an expensive operation which often requires ....

A.A. Amini, R.L. Owen, P. Anandan, and J.S. Duncan. Non-rigid motion models for tracking the left-ventricular wall. In Lecture Note in Computer Science: Information Processing in Medical Images, pages 343--356. Springer-Verlag, 1991.

....some type of spatial smoothness criterion [76] The conformal motion constraint was used by Mishra et al. 77, 78, 79, 80] to estimate LV wall surface motion from features identified in coronary angiography [77, 78, 79] and cine CT [80] image data. Another approach, proposed by Duncan et al. [81, 82, 83, 84], models the LV endocardial surface as a thin plate and tracks the motion of the surface by minimizing a cost function with penalty terms for bending energy and conformal stretching. Several authors have proposed algorithms for estimating elastic motion from an image sequence. Most of these ....

A. A. Amini, R. L. Owen, P. Anandan, and J. S. Duncan. Non-rigid motion models for tracking the left-ventricular wall. In Information Processing in Medical Imaging, Wye, England, 1991.

....groups as well as hospitals. Since its creation in 1989, our group has pioneered work in the use of deformable models to extract the left ventricle [4, 21, 5, 20, 23, 6, 3, 44, 13] Other groups as well have also made various contributions to understanding the complex deformation of the ventricle [2, 43, 1, 42, 18, 51]. Over the last ten years, many tting problems have been formulated as the minimization of an energy functional corresponding to a model of the surface [32, 14, 38, 57, 23, 40, 27] Although previous approaches based on general deformable surfaces give satisfactory results, they involve large ....

A. Amini, R. Owen, P. Anandan, and J. Duncan. Non-rigid motion models for tracking the left ventricular wall. Lecture notes in computer science: Information processing in medical images, pages 343357, 1991. Springer-Verlag.

....The first stage involves the initial estimation of the displacement vectors by modeling the contour as an elastic rod and minimizing the bending energy. In the second stage, a smooth vector flow field is obtained by refining the initial displacement vectors based on another energy function. In [3, 4], they extended their method to allow surface tracking of non rigid objects undergoing conformal motion. Cohen et al. 17] presented a method to track points on deformable contours using curvature information. High curvature points on the contour are used as landmarks to guide the matching ....

....are used as landmarks to guide the matching process. Assuming the boundaries have been successfully extracted, they formulate an energy functional which preserves the matching between high curvature points while ensuring smooth flow field everywhere. This approach appears to be very similar to [4], except that an explicit description of the mapping between the contours to be matched is provided. 5.2.3 Implicit, Low level Feature Matching In implicit matching, extraction of feature sets is not required. Instead, matching is accomplished on a global basis, where a one to one relationship ....

A. A. Amini, R. L. Owen, P. Anandan, and J. S. Duncan. Non-rigid motion models for tracking the left-ventricular wall. Information Processing in Medical Images, 12th Intl. Conf., pages 341--357, 1991.

....processing groups as well as hospitals. Since its creation in 1989, our group has pioneered work in the use of deformable models to extract the left ventricle [2, 6, 5] Other groups as well have also given various contributions to the understanding of the complex deformation of the ventricle [1, 9, 10, 11]. A parametric model is weel suited when dealing with a huge amount of data like for object tracking in a sequence of 3D images. In a previous paper [3] we introduced a parametric deformable model based on a superquadric t followed by a Free Form Deformation (FFD) We show in this paper how we ....

A. Amini, R. Owen, P. Anandan, and J. Duncan. Non-rigid motion models for tracking the left ventricular wall. In Information processing in medical images, Lecture notes in computer science, pages 343357, 1991. Springer-Verlag.

No context found.

A. Amini, R. Owen, L. Staib, P. Anandan, and J. Duncan. non-rigid motion models for tracking the left ventricular wall. Lecture notes in computer science: Information processing in medical images. 1991. Springer-Verlag.

No context found.

Amir A. Amini, R. L. Owen, P. Anandan, and James S. Duncan. Non-rigid motion models for tracking the left-ventricular wall. In Proceedings of the International Conference on Information Processing in Medical Imaging, pages 343--357, 1991.

No context found.

Amir A. Amini, R. L. Owen, P. Anandan, and James S. Duncan. Non-rigid motion models for tracking the left-ventricular wall. In Proceedings of the International Conference on Information Processing in Medical Imaging, pages 343--357, 1991.

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