Object-based 3D binary reconstruction from sparse projections in cone beam CT: Comparison of three projection operators

International audienceWe present herein a level set approach to the X-ray tomography problem with sparse projection data and study the impact of the projection operator on the binary reconstruction accuracy and computation time. The comparison is carried out on three projectors: the Separable Footprint (Trapeze-Trapeze, SF-TT) [3], a classical Raydriven (RD) and a Simplified version of the Distance-Driven (SDD) projector respectively. The performance, are evaluated for each operator, on a binary 3D Shepp-Logan phantom by varying the number of projections from 5 to 13, and considering noise free and noisy cone beam projection data

Temporal tracking of coronaries in sequences of CT volumes

Cardiovascular diseases remain a major worldwide health concern. Although significant advances have been made in heart imaging, much is still expected for improving diagnostic and better assisting interventions. On this way, our work is focused on the planning and the guidance of endovascular therapies such as cardiac resynchronization or revascularization. More precisely, its objective is to find the optimal vascular path to a given target for the insertion of tools like stimulation probes, balloons or stents. The challenge is therefore to track in 3D space and time the structures of interest in order to define the instrument trajectories. This work presents a first attempt toward the temporal tracking of coronary arteries in a sequence of CT volumes. The beating heart is highly deformed over a cardiac cycle and complex movements are present (contraction, expansion, torsion) with slow, fast and inverted episodes. The coronary arteries, relying on the myocardium, are very difficult to track due to their small diameters diameters (1 to 5 mm while the CT resolution is about 0.4 mm) on one hand and, on the other hand, the CT reconstruction artifacts corresponding to fast motion phases of the heart. Many motion extraction techniques have been derived over the two last decades and widely applied in the computer vision domain. Optical flow methods [1], bayesian filtering tracking [2] and deformable models [3] are among the most well known. However, few articles have addressed the coronary vessel tracking problem in CT volume sequences. Previous studies dealt with 2D image sequences [4-9] and few of them present an automatic method [6]. To our knowledge, the work of Shechter et al. [10] based on landmarks (forking points) is the only one really applied to 3D CT sequences....Ce travail s’inscrit dans le cadre d’une procédure de planning d’intervention endovasculaire guidée par l’image. L’objectif consiste à déterminer la trajectoire d’accès à un site particulier et implique la capacité de déterminer et caractériser les trajectoires spatiales et temporelles des vaisseaux. L’approche retenue repose sur une technique de mise en correspondance de régions associant des critères de similarité de forme et d’intensité. Une première étape a pour objectif la recherche d’un point correspondant sur le vaisseau d’intérêt dans un espace de recherche de forme sphérique. La seconde étape consiste à améliorer sa localisation en explorant les points de la ligne centrale du vaisseau sur un court segment. Dans un premier temps, la méthode est testée sur des séquences contenant des mouvements simulés linéaires et non linéaires, puis sur des séquences réelles. La méthode permet de faire face à une grande partie des difficultés rencontrées sur ce type de données. Les trajectoires des points suivis sont cohérentes entre elles et avec les autres études présentées dans la littérature

Suivi temporel des coronaires dans les séquences de volumes scanner

Ce travail s'inscrit dans le cadre d'une procédure de planning d'intervention endovasculaire guidée par l'image. L'objectif consiste à déterminer la trajectoire optimale du capteur (en terme d'évitement de plaque et positionnement optimale du cathéter) par analyse de la scène vue de l'intérieur des structures déformables en mouvement. L'approche retenue repose sur une technique de mise en correspondance de régions associant des critères de similarité de forme et d'intensité pour identifier la région contenant l'artère suivie dans les volumes et raffiner ensuite la position spatiale du cathéter à l'intérieur de l'artère. Les résultats obtenus en simulation puis sur données réelles font apparaître une bonne robustesse de l'opérateur sur des mouvements d'amplitude allant jusqu'à 1 cm entre deux instants temporels, ce qui correspond aux déplacement maximal l'on peut rencontrer en pratique sur les artères coronaires

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

Characterization of 3-D coronary tree motion from MSCT angiography.

International audienceThis paper describes a method for the characterization of coronary artery motion using multislice computed tomography (MSCT) volume sequences. Coronary trees are first extracted by a spatial vessel tracking method in each volume of MSCT sequence. A point-based matching algorithm, with feature landmarks constraint, is then applied to match the 3-D extracted centerlines between two consecutive instants over a complete cardiac cycle. The transformation functions and correspondence matrices are estimated simultaneously, and allow deformable fitting of the vessels over the volume series. Either point-based or branch-based motion features can be derived. Experiments have been conducted in order to evaluate the performance of the method with a matching error analysis

Reconstruction 3d Des Artères Coronaires En Imagerie Rotationnelle Rx

National audienceNous présentons une méthode de reconstruction 3D des artères coronaires à partir de 4 projections acquises en imagerie rotationnelle R-X. L'approche retenue considère un problème d'optimisation d'une fonction "objectif", en se basant sur un estimateur Bayésien (MAP : Maximum à postériori) et un modèle de distribution des données de projection de type Poisson. Le problème étant sous déterminé, nous introduisons un a priori afin d'améliorer la convergence de l'algorithme. Trois fonctions de régularisation sont ainsi considérées de type normes L0, L1 et L2 respectivement. Les algorithmes ont été testés sur des séquences de projections simulées à partir de séquences dynamiques d'arbres coronaires 3D extraits à partir d'examens acquis sur un scanner hélicoïdal multibarettes

Improving abdomen tumor low-dose CT images using a fast dictionary learning based processing.

International audienceIn abdomen computed tomography (CT), repeated radiation exposures are often inevitable for cancer patients who receive surgery or radiotherapy guided by CT images. Low-dose scans should thus be considered in order to avoid the harm of accumulative x-ray radiation. This work is aimed at improving abdomen tumor CT images from low-dose scans by using a fast dictionary learning (DL) based processing. Stemming from sparse representation theory, the proposed patch-based DL approach allows effective suppression of both mottled noise and streak artifacts. The experiments carried out on clinical data show that the proposed method brings encouraging improvements in abdomen low-dose CT images with tumors

Thoracic low-dose CT image processing using an artifact suppressed large-scale nonlocal means.

International audienceThe x-ray exposure to patients has become a major concern in computed tomography (CT) and minimizing the radiation exposure has been one of the major efforts in the CT field. Due to plenty high-attenuation tissues in the human chest, under low-dose scan protocols, thoracic low-dose CT (LDCT) images tend to be severely degraded by excessive mottled noise and non-stationary streak artifacts. Their removal is rather a challenging task because the streak artifacts with directional prominence are often hard to discriminate from the attenuation information of normal tissues. This paper describes a two-step processing scheme called 'artifact suppressed large-scale nonlocal means' for suppressing both noise and artifacts in thoracic LDCT images. Specific scale and direction properties were exploited to discriminate the noise and artifacts from image structures. Parallel implementation has been introduced to speed up the whole processing by more than 100 times. Phantom and patient CT images were both acquired for evaluation purpose. Comparative qualitative and quantitative analyses were both performed that allows conclusion on the efficacy of our method in improving thoracic LDCT data

Sparse reconstruction from a limited projection number of the coronary artery tree in X-ray rotational imaging

International audienceThis paper deals with the 3D reconstruction of sparse data in X-ray rotational imaging. Due to the cardiac motion, the number of available projections for this reconstruction is equal to four, which leads to a strongly undersampled reconstruction problem. We address thus this illness problem through a regularized iterative method. The whole algorithm is divided into two steps. Firstly, a minimal path segmentation step extracts artery tree boundaries. Secondly, a MAP reconstruction comparing L0-norm and L1-norm priors is applied on this extracted coronary tree. The reconstruction optimization process relies on a separable paraboloidal (SPS) algorithm. Some preliminary results are provided on simulated rotational angiograms