R.T. Constable, K.M. Rath, A.J. Sinusas, and J.C. Gore, \Development and evaluation of tracking algorithms for cardiac wall motion analysis using phase velocity MR imaging," Magnetic Resonance in Medicine 32(1), pp. 33-42, 1994.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....periodicity in time is not guaranteed. Only a few studies impose temporal continuity or periodicity in their model: these studies deal with segmentation of 2D (O Donnell et al. 1994) or 3D images (de Murcia, 1996; Matheny and Goldgof, 1995; Schudy and Ballard, 1979) Some other rare methods in 2D (Todd Constable et al. 1994; McEachen et al. 1994) or in 3D (Thirion, 1995; Nastar, 1994) perform a posteriori time filtering. Moreover, all these tracking techniques ( Park et al. 1996; Park et al. 1994) excepted) do not provide intuitive parameters describing characteristic motions without non trivial computation ....

Todd Constable, R.T., Rath, K.M., Sinusas, A.J., and Gore, J.C. (1994). Development and evaluation of tracking algorithms for cardiac wall motion analysis using phase velocity MR imaging. In Magnetic Resonance Medicine, Vol. 32, pp. 33--42.

.... tags [73,101,1,74,67] Another MRI technique called phase contrast MRI, which produces images of cardiac tissue velocity [69] has recently emerged as a technique to study heart motion, and has spawned a variety of deformable modeling techniques which attempt to characterize the cardiac motion [18,58]. Techniques such as these differ considerably in the feature mapping component of the deformable model algorithm, but they share much in common with the techniques used to constrain the solution set of allowable motions. 2.5. Perspectives on Related Work An optical flow based technique is ....

R T Constable, K M Rath, A J Sinusas, and J C Gore. "Development and evaluation of tracking algorithms for cardiac wall motion analysis using phase velocity MR imaging." Magn Reson Med, 32:33--42, 1994.

....the volumetric image using conservation of dioeerential elements of isophotes [5] or using similarities of the intensity levels [25] Unfortunately, because the correspondence is dened between two successive images, regularity and periodicity in time is not guaranteed. Only a few studies in 2D [26, 14] or in 3D [17, 25] perform a posteriori time ltering. Moreover, these methods ( 19, 18] excepted) do not provide intuitive parameters describing characteristic motions without non trivial computation [3, 4, 28] The 4D polar transformation dened in this article aims to achieve four goals: 1. to ....

R.T. Todd Constable, K.M. Rath, A.J. Sinusas, and J.C. Gore. Development and Evaluation of Tracking Algorithms for Cardiac Wall Motion Analysis Using Phase Velocity MR Imaging. In Magnetic Resonance Medicine, volume 32, pages 3342, 1994.

....yield obtained by integrating these methods with geometric models, such as the one of this paper, appears significant. Phase contrast approaches to MRI motion analysis have shown promising gains over previous MR signal encoding techniques such as spin tagging [23] Van Dijk and others [24] [27] have suggested use of the MR phase to record cardiac wall velocity measurements using a spin echo gated MR imaging sequence. The phase contrast method in itself is does not appear suitable for tracking point wise trajectories along the LV wall due to the noise associated with nonhomogeneous ....

R. T. Constable, K. M. Rath, A. J. Sinusas, and J. C. Gore, "Development and evaluation of tracking algorithms for cardiac wall motion analysis using phase velocity mr imaging," Magn. Reson. Med., vol. 32, pp. 33--42, 1994.

....to assist our traditional shape based correspondence method ( 3] in refining our point wise estimate of the frame to frame trajectories. We show that this method is particularly useful in regions with limited shape variation. The work in this paper is based on previous efforts in [4] 5] and [6]. Background The ability to track points on object surfaces over time has been a principal goal of both rigid and non rigid motion research in the field of computer vision. Snakes, or active contour models, have been the primary focus of many recent efforts (e.g. 7] 8] and [9] This method ....

....imaging sequence. Since then others ( 20] 21] have shown that velocity information can be encoded into the phase of the NMR signal and incorporated into a conventional cine sequence. Additionally, methods have been developed for tracking cardiac wall motion based solely on these velocity maps ([6]) In phase contrast cine MRI the spectrometer cycles at a constant rate (asynchronous to the cardiac cycle) with timing of the phase encoding increments driven by the cardiac cycle trigger. 3 Two sequences that interrogate the same section but contain different flow encoding are interleaved ....

R. Todd Constable, Kristina M. Rath, Albert J. Sinusas, and John C. Gore. Development and evaluation of tracking algorithms for cardiac wall motion analysis using phase velocity MR imaging. Magnetic Resonance in Medicine, 32:33--42, 1994.

....describe the state of a deformed material. A suitable measure of deformation is provided by the strain tensor, or the rate of deformation tensor [15] With the availability of dense 3 D velocity maps, estimating the rate of deformation of the myocardium becomes possible. Recently the authors in [4, 12] have demonstrated that velocity maps in three orthogonal directions can be measured at multiple instants throughout the cardiac cycle. This new tech 2 FRANCOIS G. MEYER et al. nique, termed phase contrast cine magnetic resonance imaging, combines phase contrast imaging methods with cardiac ....

....velocity of the particle. If we iterate this scheme again, errors in particle positions will grow rapidly in time. Another related problem stems from the fact that any noise in the velocity will be transmitted to the position estimates. These errors may also accumulate over time. The authors in [4, 12] have encountered these difficulties when tracking small isolated regions of interest in the myocardium using phase contrast MRI velocities. They have tried to correct them by forward and reverse integration in time. Establishing trajectories of the same material points from a sequence of images ....

[Article contains additional citation context not shown here]

R.T. Constable, K.M. Rath, A.J. Sinusas, and J.C. Gore. Development and evaluation of tracking algorithms for cardiac wall motion analysis using phase velocity MR imaging. Magnetic Resonance in Medecine, Vol. 32:33--42, 1994.

....to assist our traditional shape based correspondence method ( 2] in refining our point wise estimate of the frame to frame trajectories. We show that this method is particularly useful in regions with limited shape variation. The work in this paper is based on previous efforts in [3] and [4]. 1.1 Background The ability to track points on object surfaces over time has been a principal goal of both rigid and non rigid motion research in the field of computer vision. Snakes, or active contour models, have been the primary focus of many recent efforts (e.g. 5] All of these methods ....

....encoding techniques such as spin tagging. Van Dijk ( 10] first suggested use of the NMR phase to record cardiac wall ve locity measurements using a spin echo gated MR imaging sequence. Since then methods have been developed for tracking cardiac wall motion based solely on these velocity maps ([4]) In cardiac MRI analysis, these velocity maps have been shown to be highly accurate for regions embedded in the myocardium. Unfortunately, pixels near the boundaries of the LV become influenced by the spectral content of surrounding non homogeneous material resulting in a considerable number of ....

R. Todd Constable, Kristina M. Rath, Albert J. Sinusas, and John C. Gore. Development and evaluation of tracking algorithms for cardiac wall motion analysis using phase velocity mr imaging. Magnetic Resonance in Medicine, 32:33--42, 1994.

....These methods rely on two stages. First the instantaneous velocity is estimated everywhere inside the object of interest. The velocity can be estimated from the spatiotemporal variation of the intensity function [16] 9] 17] or it can be directly calculated from the imaging technique [18] [19], 1] The second stage is the motion recovery from the temporal sequence of snapshots of the velocity fields. The difficulty arise from the fact that Eulerian (or spatial) velocity fields are measured with a large time step, and we want to recover the Lagrangian path of each point in the object. ....

....is only given on a discrete grid with limited resolution. Interpolation schemes are required to estimate velocities at positions not on the grid [20] Finally any noise in the velocity will be transmitted to the position estimates. These errors may also accumulate over time. The authors in [19], 21] 22] have encountered these difficulties when tracking pixels, or clusters of pixels in the myocardium using phase contrast MRI velocities. They have tried to correct them by forward and reverse integration in time. In fact one of the major limitations of our initial effort [19] is that ....

[Article contains additional citation context not shown here]

R.T. Constable, K.M. Rath, A.J. Sinusas, and J.C. Gore. Development and evaluation of tracking algorithms for cardiac wall motion analysis using phase velocity MR imaging. Magn. Reson. Med., Vol. 32:33--42, 1994.

No context found.

R.T. Constable, K.M. Rath, A.J. Sinusas, and J.C. Gore, \Development and evaluation of tracking algorithms for cardiac wall motion analysis using phase velocity MR imaging," Magnetic Resonance in Medicine 32(1), pp. 33-42, 1994.

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