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Real-time MRI is a novel noninvasive imaging technique that allows the visualization of physiological processes with both good spatial and temporal resolutions. However, the reconstruction of images from highly undersampled data, needed to perform real-time imaging, remains challenging. Recently, the combination of Compressed Sensing theory with motion compensation techniques has shown to achieve...
Strain and related tensors play a major role in cardiac function characterization, so correct estimation of the local phase in tagged images is crucial for quantitative myocardial motion studies. We propose an Harmonic Phase related procedure that is adaptive in the spatial and the spectral domains: as for the former, we use an angled-steered analysis window prior to the Fourier Transform; as for...
Most automatic scar segmentation methods for cardiac DE-CMR images rely on an existing myocardial segmentation (from CINE-CMR) that is registered to the DE-CMR volume, step where alignment errors are usually introduced. We present a variational method that, with the same inputs, identifies the healthy and scarred tissue and selectively corrects the endocardial and epicardial contours. For this, we...
A procedure to fuse the information of short-axis cine and late enhanced magnetic resonance images is presented. First a coherent 3D reconstruction of the images is obtained by object-based interpolation of the information of contiguous slices in stacked short-axis cine acquisitions and by the correction of slice misalignments with the aid of a set of reference long-axis slices. Then, late enhanced...
A realistic log-compressed law for ultrasound images based on a real device is proposed. The model takes into account the linear behavior of the logarithmic amplifier for small signal gain which transforms image values in a different way as the classical models do. Additionally, for recovery purposes, a method for the estimation of the compression parameters is also proposed when a realistic log-compressed...
A stochastic deformable model is proposed for the segmentation of the myocardium in Magnetic Resonance Imaging. The segmentation is posed as a probabilistic optimization problem in which the optimal time-dependent surface is obtained for the myocardium of the heart in a discrete space of locations built upon simple geometric assumptions. For this purpose, first, the left ventricle is detected by a...
This work proposes a new methodology for the extraction of Harmonic Phase images in cardiac tagged Magnetic Resonance Imaging. The procedure draws upon the use of the Windowed Fourier Transform, which provides a spatially varying representation of the signal spectra. The spectral peaks of the local Fourier domain are then extracted by a conventional Harmonic Phase recovering technique in such a way...
The diagnosis and therapy planning of high prevalence pathologies such as infantile colic can be substantially improved by statistical signal processing of activity/rest registries. Assuming that colic episodes are associated to activity episodes, diagnosis aid systems should be based on preprocessing techniques able to separate real activity from rest epochs, and feature extraction methods to identify...
In this paper we propose an alternative method to estimate and visualize the strain rate tensor (ST) in magnetic resonance images (MRI) when phase contrast MRI (PCMRI) and tagged MRI (TMRI) are not available. This alternative is based on image processing techniques. Concretely, an elastic image registration algorithm is used to estimate the movement of the myocardium at each point. Our experiments...
A segmentation application prototype of the volume of the left ventricle for Magnetic Resonance Imaging is being developed. The foundation for this work is given by modeling possible radial deformations of the epicardium and endocardium contours by means of a Markov Random Field over which the most probable configuration is estimated. The field makes use of a Bayesian approach based on a priori terms...
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