Similarity enhancement for automatic segmentation of cardiac structures in computed tomography volumes.

International audienceThe aim of this research is proposing a 3-D similarity enhancement technique useful for improving the segmentation of cardiac structures in Multi-Slice Computerized Tomography (MSCT) volumes. The similarity enhancement is obtained by subtracting the intensity of the current voxel and the gray levels of their adjacent voxels in two volumes resulting after preprocessing. Such volumes are: a. - a volume obtained after applying a Gaussian distribution and a morphological top-hat filter to the input and b. - a smoothed volume generated by processing the input with an average filter. Then, the similarity volume is used as input to a region growing algorithm. This algorithm is applied to extract the shape of cardiac structures, such as left and right ventricles, in MSCT volumes. Qualitative and quantitative results show the good performance of the proposed approach for discrimination of cardiac cavities

Medical image registration using Edgeworth-based approximation of Mutual Information

International audienceWe propose a new similarity measure for iconic medical image registration, an Edgeworth-based third order approximation of Mutual Information (MI) and named 3-EMI. Contrary to classical Edgeworth-based MI approximations, such as those proposed for inde- pendent component analysis, the 3-EMI measure is able to deal with potentially correlated variables. The performance of 3-EMI is then evaluated and compared with the Gaussian and B-Spline kernel-based estimates of MI, and the validation is leaded in three steps. First, we compare the intrinsic behavior of the measures as a function of the number of samples and the variance of an additive Gaussian noise. Then, they are evaluated in the context of multimodal rigid registration, using the RIRE data. We finally validate the use of our measure in the context of thoracic monomodal non-rigid registration, using the database proposed during the MICCAI EMPIRE10 challenge. The results show the wide range of clinical applications for which our measure can perform, including non-rigid registration which remains a challenging problem. They also demonstrate that 3-EMI outperforms classical estimates of MI for a low number of samples or a strong additive Gaussian noise. More generally, our measure gives competitive registration results, with a much lower numerical complexity compared to classical estimators such as the reference B-Spline kernel estimator, which makes 3-EMI a good candidate for fast and accurate registration tasks

Segmentation 3D multi-objets d'images scanner cardiaques : une approche multi-agents

International audienceNous proposons une nouvelle méthode de segmentation permettant une détection multi-objets, semi-interactive et à caractère générique, appliquée à l'extraction de structures cardiaques en imagerie scanner multibarettes. L'approche proposée repose sur l'élaboration d'un schéma multi-agents combiné à une méthode de classification supervisée qui permet l'introduction d'a priori dans le processus de segmentation ainsi que des temps de calcul rapides. Le système multi-agents proposé est centralisé autour d'un agent communiquant qui contrôle une population d'agents situés dans l'image dont le rôle est d'assurer la segmentation au moyen d'interactions de type coopératif et compétitif. La méthode proposée a été testée sur plusieurs bases de données patient. Quelques résultats représentatifs sont finalement présentés et discutés

A Hybrid Tissue-Level Model of the Left Ventricle: Application to the Analysis of the Regional Cardiac Function in Heart Failure

International audienceThis work contributes to the systemic interpretation of clinical data for the analysis of the regional cardiac function in the context of heart failure. A two-step patient-specific approach, combining a realistic geometry and a hybrid, tissue-level electromechanical model of the left ventricle is proposed. For the first step, a fast framework to extract a realistic geometry of the left ventricle from MSCT data is proposed. This geometry is then applied to a tissue-level model of the left ventricle, coupling a discrete electrical model, a mechanical model integrating a visco-elastic law, solved by a finite element method and a hydraulic model. A set of simulations carried out with the model are shown and preliminary results of the parameter identification approach, based on real patient data, are presented and discussed

Assessment of Left Ventricular Function in Cardiac MSCT Imaging by a 4D Hierarchical Surface-Volume Matching Process

Multislice computed tomography (MSCT) scanners offer new perspectives for cardiac kinetics evaluation with 4D dynamic sequences of high contrast and spatiotemporal resolutions. A new method is proposed for cardiac motion extraction in multislice CT. Based on a 4D hierarchical surface-volume matching process, it provides the detection of the heart left cavities along the acquired sequence and the estimation of their 3D surface velocity fields. A Markov random field model is defined to find, according to topological descriptors, the best correspondences between a 3D mesh describing the left endocardium at one time and the 3D acquired volume at the following time. The global optimization of the correspondences is realized with a multiresolution process. Results obtained on simulated and real data show the capabilities to extract clinically relevant global and local motion parameters and highlight new perspectives in cardiac computed tomography imaging

Data fusion of left ventricle Electro-Anatomic Mapping and Multislice Computerized Tomography for Cardiac Resynchronisation Therapy optimization

International audienceCardiac Resynchronization Therapy is a treatment for bi-ventricular asynchronism. It can be optimized by the identification of the most effective pacing sites. The aim of this study is to provide a helpful tool to perform this identification by the fusion of electrical and anatomical information resulting from Electro-Anatomic Mapping (EAM) data and Multislice Computerized Tomography (MSCT) imaging. EAM data provide an approximation of the left ventricle (LV) 3D-surface (SEAM). Left cardiac chambers are segmented from MSCT imaging and surfaces are reconstructed (SCT). In order to represent this information in a unified framework, a three steps method is proposed: (1) the LV is separated from the left auricle on SCT providing S'CT; (2) a semi-automatic rigid registration method is applied to SEAM and S'CT; (3) activation time delays are estimated on S'CT from the EAM data. This method results in a graphical interface offering to clinicians means to identify abnormal electrical activity sites

Coronary vein tracking from MSCT using a minimum cost path approach

International audienceIn this paper, we deal with the problem of tracking the coronary venous tree from Multi-Slice Computed Tomography (MSCT) angiography. Contrast inhomogeneities are a major issue. The proposed tracking procedure is based on minimum-cost path computation and makes use of `Fast-Marching' technique. The algorithm aims at propagating a front inside a vascular structure and extracting a centered path. To achieve this goal, a specific cost function which combines the vessel local orientation to a vesselness measure is designed. Experiments on synthetic data and real data have been performed. Coronary veins with contrast difficulties are extracted with a low computing time

Modélisation Markovienne pour l'estimation combinée de forme et de mouvement : Application au coeur en imagerie scanner multibarrette

Une méthode d'estimation conjointe de forme et de mouvement non rigide à partir de séquences temporelles tri-dimensionnelles est proposée. Basée sur une mise en correspondance surface-volume, elle permet, à partir d'une unique forme segmentée, d'estimer la forme et son mouvement sur toute la séquence. Une modélisation Markovienne combinée à un algorithme de recuit simulé estime les correspondances entre les noeuds du maillage modélisant l'objet à l'instant t et les voxels du volume à l'instant t + 1. La méthode a été appliquée à l'extraction de formes et de mouvements cardiaques en tomodensitométrie multibarrette. Les tests, réalisés sur données simulées et données réelles, ont donné des résultats prometteurs

Architecture pyramidale agent pour la segmentation d'image : Application à l'extraction d'une zone lobulaire issue d'une mammographie

Une nouvelle approche de segmentation d'image, basée d'une part sur une architecture pyramidale et d'autre part sur les concepts agent, est appliquée à des images de mammographie. Les interactions locales d'agents, modélisées par un plan d'actions comportementales assurent une segmentation progressive par fusions pertinentes de régions. L'aspect novateur de ce travail réside , entre autre, dans la transposition du graphe d'adjacence issu de la pyramide irrégulière adaptative en un réseau d'agents accointants, favorisant ainsi au mieux les choix de fusion. L'application des principes de la pyramide agent à l'extraction du tissu glandulaire en mammographie montre des résultats significatifs quant aux potentialités de cette nouvelle méthode de segmentation

Joint Shape and Motion Estimation using Markovian Fields : Application to Multislice Computed Tomography Cardiac Imaging

We propose a method for joint surface and non-rigid motion estimation from three-dimensional dynamic sequences. Based on a surface-volume matching, it provides, from one first segmented surface, both motion and deformations of the object of interest along the whole sequence. A Markovian model, combined with a simulated annealing process, estimates the correspondences between the nodes of the surface mesh modeling the object of interest at one time and the voxels of the volume representing the object at the following time. The method has been applied to cardiac surface and motion extraction in Multislice Computed Tomography. Tests realized with simulated motion and on real data have provided promising results.Une méthode d'estimation conjointe de forme et de mouvement non rigide à partir de séquences temporelles tridimensionnelles est proposée. Reposant sur une mise en correspondance surface-volume, elle permet, à partir d'une première segmentation de l'objet d'intérêt, d'estimer le mouvement de l'objet et ses déformations sur toute la séquence temporelle d'observation. Une modélisation markovienne combinée à un algorithme de recuit simulé estime les correspondances entre les noeuds du maillage de surface modélisant l'objet à un instant et les voxels du volume représentant l'objet à l'instant suivant. La méthode a été appliquée à l'extraction de formes et de mouvements cardiaques en tomodensitométrie multibarrette. Les tests, réalisés à la fois avec des mouvements simulés et sur des données réelles, ont donné des résultats prometteurs