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Biomedical ultrasound image quality is limited due to the blurring of tissue reflectivity introduced by the transducer Point Spread Function (PSF). Deconvolution techniques can be used to obtain the pure tissue response, otherwise called reflectivity function. Typically deconvolution methods are developed in the only purpose of image visual quality improvement. In this work we present an Expectation...
This paper reviews our most recent contributions in the field of cardiac deformation imaging, which includes a motion estimation framework based on the conservation of the image phase over time and an open pipeline to benchmark algorithms for cardiac strain imaging in 2D and 3D ultrasound. The paper also shows an original evaluation of the proposed motion estimation technique based on the new benchmarking...
Despite the overwhelming availability of techniques for computation of cardiac deformation and strain with 2D echocardiography, their widespread dissemination in clinical practice is still held back by the reported low reproducibility between different solutions. This can in part be attributed to the lack of a solid and open quality assurance framework to assess and compare their performance. Building...
Tracking of moving objects in an image sequence is an important task in many application (e.g. medical imaging, robotics). However, this task is usually difficult due to inherent problems that could happen in sequences (i.e. possible occlusion of the object, large interframe motion). In this paper, we describe a new approach to integrate a priori motion information into a level-set-based active contour...
In this paper we propose a compressed sensing (CS) method adapted to 3D ultrasound imaging (US). In contrast to previous work, we propose a new approach based on the use of learned overcomplete dictionaries. Such dictionaries allow for much sparser representations of the signals since they are optimized for a particular class of images such as US images. We will investigate two undersampling patterns...
This paper proposes a new simulation framework for generating realistic 3D ultrasound synthetic images that can serve for validating strain quantification algorithms. Our approach extends previous work and combines a real ultrasound sequence with synthetic biomechanical and ultrasound models. It provides images that fairly represent all typical ultrasound artifacts. Ground truth motion fields are...
Segmentation of the myocardium in echocardiographic images is an important task for the diagnosis of heart disease. This task is difficult due to the inherent problems of echographic images (i.e. low contrast, speckle noise, signal dropout, presence of shadows). In this article, we extend a level-set method recently proposed in [1] in order to track the whole myocardium in echocardiographic sequences...
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...
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...
In this paper we address the segmentation of shapes which may be approximated by two elliptical contours. Such patterns are indeed recurrent in many image processing applications. In this context, we develop a level-set framework especially dedicated to the detection of annular-like shapes. The behavior of this approach is illustrated on images from different fields. An evaluation is then performed...
This paper describes a free open source software in Matlab (named Creaseg, http://www.creatis.insa-lyon. fr/~bernard/creaseg) for the evaluation of the performance of different level-set based algorithms in the context of 2D image segmentation. The platform gives access to the implementation of six level-set methods that have been chosen in order to cover a wide range of data attachment terms (contour,...
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...
The new paradigm of service-oriented architecture leads to new requirements for software systems. These requirements must be met when integrating AI systems into a SOA landscape, too. However, most AI systems today are monolithic. In this paper we develop a general approach to provide artificial intelligence based on the concept of intelligent agents as services in a SOA landscape. Here the AI system...
A Computer-Aided Detection (CAD) scheme to support prostate cancer diagnosis based on ultrasound images is presented. The approach described in this work employs a multifeature classification model. To indentify features highly correlated to the pathologic state of the tissue we use a Feature Selection algorithm based on mutual information. System-dependent effects are removed through predictive deconvolution...
Biomedical ultrasound (US) image quality is limited due to the blurring of tissue reflectivity introduced by the transducer point spread function (PSF). Deconvolution techniques can be used to eliminate this effect and to obtain the pure tissue response. In this paper we propose a new enhancement method based on recursive least squares (RLS) adaptive filtering. The method handles the spatial variability...
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