Imaging myocardial strain

McVeigh, E.; Ozturk, Cengizhan

doi:10.1109/79.962277

Cited by 18 publications

(12 citation statements)

References 64 publications

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“…Tagged MRI has shown to produce mechanical activation maps that are closely correlated with the corresponding electrical activation maps for the LV [130], [131]. Generating electrical activation times requires an invasive approach and can be obtained only on the endocardial surface using specialized catheters, or accessible pericardial surfaces.…”

Section: Discussionmentioning

confidence: 99%

Estimating motion from MRI data

2003

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Invited Paper-Magnetic resonance imaging (MRI) is an ideal imaging modality to measure blood flow and tissue motion. It provides excellent contrast between soft tissues, and images can be acquired at positions and orientations freely defined by the user. From a temporal sequence of MR images, boundaries and edges of tissues can be tracked by image processing techniques. Additionally, MRI permits the source of the image signal to be manipulated. For example, temporary magnetic tags displaying a pattern of variable brightness may be placed in the object using MR saturation techniques, giving the user a known pattern to detect for motion tracking. The MRI signal is a modulated complex quantity, being derived from a rotating magnetic field in the form of an induced current. Well-defined patterns can also be introduced into the phase of the magnetization, and could be thought of as generalized tags. If the phase of each pixel is preserved during image reconstruction, relative phase shifts can be used to directly encode displacement, velocity and acceleration. New methods for modeling motion fields from MRI have now found application in cardiovascular and other soft tissue imaging. In this review, we shall describe the methods used for encoding, imaging, and modeling motion fields with MRI.

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Section: Discussionmentioning

confidence: 99%

Estimating motion from MRI data

2003

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“…Various approaches have been developed for quantitative regional function assessment, using both conventional and modified imaging methods. Several review articles have been previously published on the analysis of local cardiac motion from MRI . In this work, we provide an update on this important clinical application.…”

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confidence: 99%

Magnetic resonance imaging of myocardial strain: A review of current approaches

Chițiboi

Axel

2017

Magnetic Resonance Imaging

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“…[9] is described in Appendix A. 1 Note that if a priori information about is available (which is however unlikely) in the form of a pdf, p(), it can be incorporated in the optimization problem in EQ. [7] by multiplying it with p(S͉) to result in a reconstruction that is optimal in the maximum a posteriori (MAP) sense.…”

Section: Bayesian Maximum-likelihood (Ml) Reconstructionmentioning

confidence: 99%

“…[1] and assumption A2, a simple and intuitive approach is to solve a penalized LS problem to reconstruct the image from the coil measurements. Recall that LS methods coincide with ML if the error is Gaussian.…”

Section: Least Squares (Ls) With Smoothness Penaltymentioning

confidence: 99%

“…Conventionally, MRI has primarily been used for imaging of static scenarios, but recently it has also been used with great success for imaging time-varying processes. An important application of dynamic MRI is imaging of the heart and monitoring of cardiac diseases (1). Another example of dynamic imaging is functional MRI (fMRI), where the timevariability of certain chemical compositions-for example, in the brain-is investigated when the patient is subjected to an external stimulus.…”

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confidence: 99%

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Image construction methods for phased array magnetic resonance imaging

Erdoğmuş

Yan

Larsson

et al. 2004

Magnetic Resonance Imaging

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Purpose: To study image construction in phased array magnetic resonance imaging (MRI) systems from a statistical signal processing point of view. Materials and Methods:Three new approaches for image combination with multiple coils are proposed: 1) one based on the singular value decomposition of the measurement matrix, which is asymptotically optimal in the signal-tonoise ratio sense; 2) one based on a maximum-likelihood formulation, incorporating a priori information on the coil sensitivities in a Bayesian manner; and 3) one based on a least-squares formulation, which incorporates a smoothness constraint on the coil sensitivities. Results:Numerical examples using synthetic and real data are presented to illustrate the performance of these new approaches. Results on the synthetic data show improvement in signal-to-error ratio, while results on the real data (a 4.7 T four-coil image of a cat spinal cord) show that the proposed methods can improve the SNR in the final image by up to 3 dB in the regions of interest compared to conventional sum-of-squares processing. Conclusion:It is demonstrated that phased array MRI reconstruction performance can be improved by the use of more elaborate statistical signal processing algorithms.

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Imaging myocardial strain

Cited by 18 publications

References 64 publications

Estimating motion from MRI data

Estimating motion from MRI data

Magnetic resonance imaging of myocardial strain: A review of current approaches

Image construction methods for phased array magnetic resonance imaging

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