Cardiac motion assessement from echocardiographic image sequences by means of the structure multivector

International audienceWe recently contributed an algorithm for the estimation of cardiac deformation from echocardiographic image sequences based on the monogenic signal. By exploiting the phase information instead of the pixel intensity, the algorithm was robust to the temporal contrast variations normally encountered in cardiac ultrasound. In this paper we propose an improvement of that framework making use of an extension of the monogenic signal formalism, called structure multivector. The structure multivector models the image as the superposition of two perpendicular waves with associated amplitude, phase and orientation. Such a model is well adapted to describe the granular pattern of the characteristic speckle noise. The displacement is computed by solving the optical flow equation jointly for the two image phases. A local affine model accounts for typical cardiac motions as contraction/expansion and shearing; a coarse-to-fine B-spline scheme allows for a robust and effective computation of the model parameters and a pyramidal refinement scheme helps deal with large motions. Performance was evaluated on realistic simulated cardiac ultrasound sequences and compared to our previous monogenic-based algorithm and classical speckle tracking. Endpoint-error was used as accuracy metric. With respect to them we achieved error reductions of 13% and 30% respectively

Medical ultrasound image reconstruction using distributed compressive sampling

International audienceThis paper investigates ultrasound (US) radiofrequency (RF) signal recovery using the distributed compressed sampling framework. The “correlation” between the RF signals forming a RF image is exploited by assuming that they have the same sparse support in the 1D Fourier transform, with different coefficient values. The method is evaluated using an experimental US image. The results obtained are shown to improve a previously proposed recovery method, where the correlation between RF signals was taken into account by assuming the 2D Fourier transform of the RF image sparse

The role of the image phase in cardiac strain imaging

International audienceThis 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 pipeline

Parallel integral projection transform for straight electrode localization in 3-D ultrasound images

In surgical practice, small metallic instruments are frequently used to perform various tasks inside the human body. We address the problem of their accurate localization in the tissue. Recent experiments using medical ultrasound have shown that this modality is suitable for real-time visualization of anatomical structures as well as the position of surgical instruments. We propose an image- processing algorithm that permits automatic estimation of the position of a line-segment-shaped object. This method was applied to the localization of a thin metallic electrode in biological tissue. We show that the electrode axis can be found through maximizing the parallel integral projection transform that is a form of the Radon transform. To accelerate this step, hierarchical mesh-grid algorithm is implemented. Once the axis position is known, localization of the electrode tip is performed. The method was tested on simulated images, on ultrasound images of a tissue mimicking phantom containing a metallic electrode, and on real ultrasound images from breast biopsy. The results indicate that the algorithm is robust with respect to variations in electrode position and speckle noise. Localization accuracy is of the order of hundreds of micrometers and is comparable to the ultrasound system axial resolution

Bilinear modelling and estimation of displacement for thyroid cancer elasticity imaging

In this study we present a tissue motion modelling and estimation method for elasticity imaging with ultrasound applied to thyroid cancer. Elasticity image of tumor and surrounding tissue of thyroid gland is acquired under a freehand tissue compression using a standard ultrasound probe. The complexity of the movements to analyze requires the development of a parametric model of the displacement and a specific estimation method adapted to sub-pixel displacement. The motion model is a bilinear model with 8 parameters. The model parameters are estimated using a multi-scale iterative approach. This approach was tested on simulation images and clinical data. The first clinical results show the interest and the potential of such imaging technique for the visualization of thyroid tumors.Nous proposons dans cette étude une modélisation et une estimation du mouvement pour l’imagerie échographique de l’élasticité des tissus mous appliquée au diagnostic du cancer de la thyroïde. L’image de l’élasticité de la tumeur et des tissus environnants s’obtient par compression progressive de la thyroïde du patient à l’aide de la sonde échographique. La complexité des mouvements à analyser nécessite le développement d’un modèle paramétrique du déplacement et d’une méthode d’estimation des paramètres du modèle adaptée aux déplacements sub-pixels. Le modèle de mouvement est un modèle bilinéaire à 8 paramètres. L’estimation des paramètres du modèle s’effectue par une approche itérative multi-échelle. Cette approche est testée sur des images de simulation puis, sur des données cliniques. Les premiers résultats cliniques indiquent l’intérêt et le potentiel de cette technique d’imagerie pour la visualisation des tumeurs de la thyroïde

OntoVIP: An ontology for the annotation of object models used for medical image simulation.

International audienceThis paper describes the creation of a comprehensive conceptualization of object models used in medical image simulation, suitable for major imaging modalities and simulators. The goal is to create an application ontology that can be used to annotate the models in a repository integrated in the Virtual Imaging Platform (VIP), to facilitate their sharing and reuse. Annotations make the anatomical, physiological and pathophysiological content of the object models explicit. In such an interdisciplinary context we chose to rely on a common integration framework provided by a foundational ontology, that facilitates the consistent integration of the various modules extracted from several existing ontologies, i.e. FMA, PATO, MPATH, RadLex and ChEBI. Emphasis is put on methodology for achieving this extraction and integration. The most salient aspects of the ontology are presented, especially the organization in model layers, as well as its use to browse and query the model repository

A virtual imaging platform for multi-modality medical image simulation.

International audienceThis paper presents the Virtual Imaging Platform (VIP), a platform accessible at http://vip.creatis.insa-lyon.fr to facilitate the sharing of object models and medical image simulators, and to provide access to distributed computing and storage resources. A complete overview is presented, describing the ontologies designed to share models in a common repository, the workflow template used to integrate simulators, and the tools and strategies used to exploit computing and storage resources. Simulation results obtained in four image modalities and with different models show that VIP is versatile and robust enough to support large simulations. The platform currently has 200 registered users who consumed 33 years of CPU time in 2011

Synthèse de réponse impulsionnelle en imagerie ultrasonore pour l\u27estimation vectorielle du déplacement

Le travail de cette thèse concerne l\u27imagerie de l\u27élasticité des tissus biologiques par échographie, également appelé élastographie ultrasonore. Le principe de cette méthode consiste à estimer, par traitement du signal et de l\u27image, le déplacement ou la déformation qui apparaît au sein d\u27un tissu lorsque celui-ci est soumis à une contrainte mécanique externe. Ce travail propose une méthode d\u27estimation du vecteur déplacement entre deux images échographiques basée sur l\u27étude de la phase de la corrélation complexe entre des signaux issus d\u27images ultrasonores. La formation de l\u27image est adaptée aux exigences de l\u27estimateur et en particulier une réponse impulsionnelle présentant des oscillations dans les deux directions de l\u27image est synthétisée. La qualité des cartes de déplacements estimées est grandement améliorée grâce à l\u27utilisation de cette réponse impulsionnelle. Des résultats de simulation et une étude expérimentale menée sur un échographe danois dédié à la recherche illustrent le travail

Back-propagation based beamformer design for Transverse Oscillations in Echocardiography

International audienceTransverse oscillation (TO) imaging is a technique that produces ultrasound radiofrequency images featuring oscillations in both spatial dimensions. This is natural for axial direction but necessitates specific beamforming for transverse direction. Conventional TO beamformer design using Fraunhofer approximation (FA) has been properly developed in linear geometry. Using cosine function modulated by Gaussian as a lateral profile, the apodization function defined as inverse Fourier transform of the profile thus corresponds to the convolution between a Gaussian and two Dirac. This approach works well in linear geometry but is limited for sector scan as in echocardiography. We propose to use back-propagation based on reciprocity theorem, which appropriately takes into account the fact that the expected oscillation profiles are in polar coordinate. To validate with simulations using Filled II, the comparison of PSFs obtained using FA and back-propagation with theoretical profiles is quantified using root mean square error. The result clearly shows that PSFs obtained using back-propagation are more accurate than using FA. But it has declining advantages than FA at larger depth because the transformation from Cartesian to polar coordinate becomes closer for FA. The next step is to validate that the obtained PSF and associated TO allow more accurate motion estimates

Tracking biopsy needle using Kalman filter and RANSAC algorithm with 3D ultrasound

International audienceRANSAC algorithm has been implemented for the detection of micro-tools (biopsy metallic needles) inserted in human tissue, and this method has the capacity to detect the position of the needle in real time. However, RANSAC algorithm depends on randomly selected models so that the robustness is poor. Therefore, a Kalman filter has been added in order to increase the stability, and realize an application in a dynamic situation. A constant velocity model was chosen for the Kalman filter. The result from RANSAC algorithm (estimate tip position of needle) was set as one part of the measurement vector. Because the speed of insertion is unknown, the speckle tracking method was added to measure the inserting speed, which is another measurement for Kalman filter. The predicted tip position of Kalman filter was compared with that of RANSAC result. The simulation has been done with the simulated volume in both static situation and dynamic situation. The result shows that in static situation, the root mean square error (RMSE) of Kalman was reduced 44.79% compared with RANSAC; in dynamic situation, the RMSE of Kalman filter was reduce by 26.5%