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The segmentation of the myocardium in echocardiographic images is an important task for the diagnosis of heart diseases. This step is made difficult due to the inherent problems of echographic images (e.g. low contrast, speckle noise). In this article, we propose a method to segment the whole myocardium (endocardium and epicardium) from 2D echographic scans. This is achieved using a level-set model...
Active geometric functions were recently introduced as a tool to perform real time 3-D segmentation. In the present paper we propose a B-spline formulation of the problem, which further improves the computational efficiency of the algorithm. We also introduce local region based energies, overcoming the limitations of the original method. The feasibility of real-time 3D segmentation in challenging...
In this study, we investigate the possibility of applying a continuous-time ARMA (CARMA) model to radio-frequency ultrasound signals. We consider the effect of the discretization process on the parameters of the continuous system, and we take into account the exponential nature of the autocorrelation function of the model to derive continuous-domain information from the parameters of the discrete...
Level-sets methods have successfully been used for segmentation of the endocardial border in cardiac US images. Robust methods have been proposed within a Bayesian framework. However, segmentation of the whole myocardial wall is still challenging given that the epicardial boundary is highly heterogeneous and discontinuous. The presence of papillary muscles may also complicate endocardial boundary...
We have recently proposed a new level-set formulation, where the level-set is modelled as a continuous parametric function expressed in a B-spline basis. We propose in this paper to adapt this formalism to the class of narrow-band level-set methods, where the implicit function evolves only around its zero-level. For this purpose, we propose to model the interface by two lists of boundary points and...
In this paper, we present a study on motion tracking in echocardiographic ultrasound images. The difficulty of motion estimation is linked to the fact that echographic image formation induces decorrelation between the underlying motion of tissue and the observed speckle motion. We investigate in this work the influence of speckle decorrelation on motion estimation from realistic simulations using...
In this paper we present a feasibility study of transverse oscillations in the field of echocardiography. Transverse oscillations beamforming methods have been shown to be able to improve the accuracy of local motion estimation with ultrasound images. This has only been studied for linear geometry while this paper shows the feasibility for sectorial geometry used in echocardiography. The possibility...
We present a simple, robust and computationally efficient method for the semi-automatic segmentation of the prostate in TRUS (Transrectal Ultrasound) image. The method relies on a variational formulation based on a deformable super- ellipse and a region energy based on the assumption of a Rayleigh distribution. Instead of using the classical level-set approach, we directly insert the implicit representation...
In the field of image segmentation, most of level-set-based active contour approaches are based on a discrete representation of the associated implicit function. We present in this paper a different formulation where the level-set is modelled as a continuous parametric function expressed on a B-spline basis. Starting from the Mumford-Shah energy functional, we show that this formulation allows computing...
In this paper we present a study for designing realistic ultrasound image simulations from a statistical point of view. Indeed it is extremely important to be able to compute realistic simulated images for validating segmentation or classification methods based on the statistics of ultrasound images. The statistics of the radio frequency (RF) signals is modeled by a distribution called K-RF distribution...
We study in this work the statistics of the radio frequency (RF) signal for both fully and partially developed speckle in echocardiographic images in the context of image segmentation and classification. From physical image formation model, we first derive the probability density function (PDF) of the RF signal using the K distribution framework. We then show that this pdf may be reliably approximated...
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