Denoising human cardiac diffusion tensor magnetic resonance images using sparse representation combined with segmentation.

Cardiac diffusion tensor magnetic resonance imaging (DT-MRI) is noise sensitive, and the noise can induce numerous systematic errors in subsequent parameter calculations. This paper proposes a sparse representation-based method for denoising cardiac DT-MRI images. The method first generates a dictionary of multiple bases according to the features of the observed image. A segmentation algorithm based on nonstationary degree detector is then introduced to make the selection of atoms in the dictionary adapted to the image's features. The denoising is achieved by gradually approximating the underlying image using the atoms selected from the generated dictionary. The results on both simulated image and real cardiac DT-MRI images from ex vivo human hearts show that the proposed denoising method performs better than conventional denoising techniques by preserving image contrast and fine structures.

Partitioning medical image databases for content-based queries on a Grid.

OBJECTIVES: In this paper we study the impact of executing a medical image database query application on the grid. For lowering the total computation time, the image database is partitioned into subsets to be processed on different grid nodes. METHODS: A theoretical model of the application complexity and estimates of the grid execution overhead are used to efficiently partition the database. RESULTS: We show results demonstrating that smart partitioning of the database can lead to significant improvements in terms of total computation time. CONCLUSIONS: Grids are promising for content-based image retrieval in medical databases.

Fusion of cine magnetic resonance and contrast-enhanced first-pass magnetic resonance data in patients with coronary artery disease: a feasibility study.

RATIONALE AND OBJECTIVES: The left ventricle (LV) myocardial wall contractibility can be evaluated using cine magnetic resonance imaging (MRI) in a qualitative or quantitative manner. Meanwhile, myocardial perfusion can be assessed using contrast-enhanced first-pass MRI. The authors propose a method of automatically fusing the complementary information from these two cardiac MRI modalities into one single image, from which a match or mismatch between contraction and perfusion could be extracted. METHODS: The authors developed a registration algorithm based on the combined use of the global affine transformation and intrinsic landmarks to match images from the same sequence or from two imaging sequences. Contraction and perfusion information was fused by combining a myocardial contour image and a parametric image of the slope of the intensity-time curve, respectively. The fusion paradigm was applied to four patients' data as a demonstration of feasibility of the proposed approach and as a preliminary evaluation. RESULTS: Cine MR and contrast-enhanced MR images were well aligned. The contractibility of the LV was displayed by the myocardial contour image. The parametric slope image was consistent with the known coronary artery status of each patient. The combined contraction-perfusion representation of the LV showed the correspondence between regional LV contraction and myocardial perfusion at a one slice level. CONCLUSIONS: Left ventricle contraction and myocardial perfusion can be represented conjointly in one single fused image. The fusion paradigm should be evaluated for a larger number of patients to evaluate the clinical relevance of this approach in assessing coronary artery disease.

Tracking geometrical descriptors on 3-D deformable surfaces: application to the left-ventricular surface of the heart.

Motion and deformation analysis of the myocardium are of utmost interest in cardiac imaging. Part of the, research is devoted to the estimation of the heart function by analysis of the shape changes of the left-ventricular endocardial surface. However, most clinically used shape-based approaches are often two-dimensional (2-D) and based on the analysis of the shape at only two cardiac instants. Three-dimensional (3-D) approaches generally make restrictive hypothesis about the actual endocardium motion to be able to recover a point-to-point correspondence between two surfaces. The present work is a first step toward the automatic spatio-temporal analysis and recognition of deformable surfaces. A curvature-based and easily interpretable description of the surfaces is derived. Based on this description, shape dynamics is first globally estimated through the temporal shape spectra. Second, a regional curvature-based tracking approach is proposed assuming a smooth deformation. It combines geometrical and spatial information in order to analyze a specific endocardial region. These methods are applied both on true 3-D X-ray data and on simulated normal and abnormal left ventricles. The results are coherent and easily interpretable. Shape dynamics estimations and comparisons between deformable object sequences are now possible through these techniques. This promising framework is a suitable tool for a complete regional description of deformable surfaces.

Reconstruction of 3-D geometry using 2-D profiles and a geometric prior model.

A method has been developed to reconstruct three-dimensional (3-D) surfaces from two-dimensional (2-D) projection data. It is used to produce individualized boundary element models, consisting of thorax and lung surfaces, for electro- and magnetocardiographic inverse problems. Two orthogonal projections are utilized. A geometrical prior model, built using segmented magnetic resonance images, is deformed according to profiles segmented from projection images. In our method, virtual X-ray images of the prior model are first constructed by simulating real X-ray imaging. The 2-D profiles of the model are segmented from the projections and elastically matched with the profiles segmented from patient data. The displacement vectors produced by the elastic 2-D matching are back projected onto the 3-D surface of the prior model. Finally, the model is deformed, using the back-projected vectors. Two different deformation methods are proposed. The accuracy of the method is validated by a simulation. The average reconstruction error of a thorax and lungs was 1.22 voxels, corresponding to about 5 mm.

Automated myocardial edge detection from breath-hold cine-MR images: evaluation of left ventricular volumes and mass.

This paper describes an automated edge detection method for the delineation of the endo- and epicardial borders of the left ventricle from magnetic resonance (MR) images. The feasibility of this technique was demonstrated by processing temporal series of cardiac MR images obtained in 12 healthy subjects and acquired from the apex to the base of the heart in multiple anatomic short axis planes with a breath-hold cine-MR acquisition sequence. This procedure allows the entire heart to be imaged in less than 5 min. The automatic program correctly identified the edges in most cases. In poor contrasted images, a fast and user-friendly interactive procedure was used to correct the border delineation. The proposed method for the contour tracing requires a limited degree of control by the user and thus considerably reduces the tedious and long operator time inherent in the usual manual contour tracing tool. The left ventricular volumes were directly measured from these sets of contours by using the Simpson rule, allowing the end-diastolic volumes (EDV), the end-systolic volumes (ESV), the ejection fraction (EF) and the myocardial mass to be determined. The values measured in this study with the dedicated software were similar to the literature values (EDV = 78.3 ml/m2; ESV = 21.1 ml/m2; EF = 73%). Associated with the ultrafast breath-hold cine-MR imaging, the described edge detection method provides an efficient clinical tool for the direct assessment of cardiac function.

Comparison between qualitative and quantitative wall motion analyses using dipyridamole stress breath-hold cine magnetic resonance imaging in patients with severe coronary artery stenosis.

Breath-hold cine magnetic resonance imaging (MRI) at rest and during dipyridamole infusion was used to study wall motion abnormalities in patients with severe coronary artery stenosis proven by coronary angiography. Sixteen patients without myocardial infarction but at least one major coronary artery with > or = 70% diameter narrowing were included. Qualitative "visual" assessment of wall motion, as well as quantitative measurement "wall thickening changes (%)" were compared using receiver operating characteristic curve analysis. 201Tl-single-photon emission computed tomography (SPECT) was also studied for comparison. Using qualitative analysis, coronary artery disease detection rate was comparable when assessing wall motion abnormalities with dipyridamole-MRI (79%) and with dipyridamole-induced perfusion defects with 201-thallium-SPECT (75%). Furthermore, sensitivity and specificity for identification of all diseased coronary territories were comparable for both imaging modalities (sensitivity of dipyridamole-MRI and 201thallium-SPECT, 80% vs. 69%; specificity, 75% vs. 80%). The quantitative method has a substantially higher sensitivity than the qualitative method in identifying all diseased territories (Az = 0.81, p < 0.01 vs. Az = 0.55 and 0.59). In addition, we demonstrated that the quantitative method had higher performance than the qualitative one in identifying the diseased vessels territories related to 1-vessel, 2-vessel, and each of individual coronary artery stenoses.

Artifacts in intravascular ultrasound imaging: analyses and implications.

The ability of an intravascular ultrasound catheter to give cross-sectional images of vessel walls and surrounding tissues, and the behavior of ultrasound in heterogeneous media, are at the origin of degradation of image quality. Qualitative and quantitative analyses of in vivo studies are then operator-dependent and are limited by artifacts. We investigated these limitations by an in vitro study on plexiglass phantoms and segments of fresh arteries. We used a 20 MHz transducer mounted on the tip of a 4.8 F catheter and an interventional ultrasound system. The ultrasound beam is reflected onto the rotating transducer at 600 rotations per minute (RPM), creating 360 degrees real-time images (10 images/second). We then observed, analyzed and interpreted the most specific reasons for image artifacts: geometric distortions, multiple echoes, the point spread function (PSF) of the imaging system, near-field effects, "petal-shaped" effect, and ultrasound speckle. Various practical implications have resulted from this study. Only a thorough knowledge of how to avoid some of the most obvious pitfalls will enable the user to obtain maximum benefits from intravascular ultrasound imaging, and to appreciate its limitations.

The effect of geometric and topologic differences in boundary element models on magnetocardiographic localization accuracy.

This study was performed to evaluate the changes in magnetocardiographic (MCG) source localization results when the geometry and the topology of the volume conductor model were altered. Boundary element volume conductor models of three patients were first constructed. These so-called reference torso models were then manipulated to mimic various sources of error in the measurement and analysis procedures. Next, equivalent current dipole localizations were calculated from simulated and measured multichannel MCG data. The localizations obtained with the reference models were regarded as the "gold standard." The effect of each modification was investigated by calculating three-dimensional distances from the gold standard localizations to the locations obtained with the modified model. The results show that the effect of the lungs and the intra-ventricular blood masses is significant for deep source locations and, therefore, the torso model should preferably contain internal inhomogeneities. However, superficial sources could be localized within a few millimeters even with nonindividual, so called standard torso models. In addition, the torso model should extend long enough in the pelvic region, and the positions of the lungs and the ventricles inside the model should be known in order to obtain accurate localizations.

Effects of radiofrequency catheter ablation on patients with permanent pacemakers.

The objective of this study was to assess the effects of radiofrequency energy application on implanted pacemaker functions. Radiofrequency (RF) catheter ablation may cause pacemaker dysfunction due to electromagnetic interferences. The effects of RF on pacemaker behavior were studied in a series of 38 pacemakers, implanted 18 +/- 26 months prior to a RF procedure using either a right ventricular approach (AV node ablation, n = 35) or a left ventricular approach (left concealed accessory pathway ablation, n = 1; VT ablation, n = 2). The 38 patients (mean age 65 +/- 9 years) included 20 men and 18 women. Before energy applications, the 23 different pacemaker models were programmed to the VVI mode at the lowest available rate. The continuous surface ECG was recorded throughout the procedure. Thorough testing of the devices was performed before and after each RF delivery. Unusual pacemaker responses occurred in 20 of the 38 cases studied (53%). The impact of RF delivery was unpredictable, and variable dysfunctions were observed at different times for a given patient or could vary for a given model. Unusual pacemaker responses included pacemaker inhibition (n = 8), untoggled backup mode (n = 3), electromagnetic interference noise mode (n = 3), temporary RF-induced pacemaker tachycardia (n = 2), erratic behavior (n = 1), oversensing of RF onset and offset (n = 8), and transient loss of ventricular capture, (n = 1). Postablation, most devices automatically toggled back to full functionality. The three devices in the untoggled backup mode had to be reprogrammed to obtain normal operations. At the end of the procedure, pacing thresholds remained unchanged in all but one patient, in whom the increase in ventricular threshold was due to a nicked lead. In conclusion, implanted pacemakers frequently exhibit transient, unpredictable responses to RF energy application. Although all pacemaker functions were restored postablation, some devices had to be reset manually. The anomalies observed during the RF application argue for the simultaneous use of an external pacemaker in pacing-dependent patients.

Modeling the 3D coronary tree for labeling purposes.

Coronary artery diseases are usually revealed using X-ray angiographies. Such images are complex to analyze because they provide a 2D projection of a 3D object. Medical diagnosis suffers from inter- and intra-clinician variability. Therefore, reliable software for the 3D reconstruction and labeling of the coronary tree is strongly desired. It requires the matching of the vessels in the different available angiograms, and an approach which identifies the arteries by their anatomical names is a way to solve this difficult problem. This paper focuses on the automatic labeling of the left coronary tree in X-ray angiography. Our approach is based on a 3D topological model, built from the 3D anthropomorphic phantom, Coronix. The phantom is projected under different angles of view to provide a data base of 2D topological models. On the other hand, the vessel skeleton is extracted from the patient's angiogram. The algorithm compares the skeleton with the 2D topological model which has the most similar vascular net shape. The method performs in a hierarchical manner, first labeling the main artery, then the sub-branches. It handles inter-individual anatomical variations, segmentation errors and image ambiguities. We tested the method on standard angiograms of Coronix and on clinical examinations of nine patients. We demonstrated successful scores of 90% correct labeling for the main arteries and 60% for the sub-branches. The method appears to be particularly efficient for the arteries in focus. It is therefore a very promising tool for the automatic 3D reconstruction of the coronary tree from monoplane temporal angiographic clinical sequences.

Estimation of three-dimensional cardiac velocity fields: assessment of a differential method and application to three-dimensional CT data.

We have investigated an optical flow method for the estimation of the three-dimensional endocardial wall motion from high-resolution X-ray CT data. This method was originally proposed by Song and Leahy. It is based on the optical flow, the divergence-free and the smoothness constraints. Due to the characteristics of the imaging modality, we studied the restriction of this approach to the boundary of the left ventricular (LV) cavity. The behaviour of the method is quantified through simulations approximating the overall motion of the LV cavity through an affine transform involving a dilation and a rotation. The method implies the choice of three parameters weighting the constraints. The results show a weak dependence of the velocity field on the weighting of the optical flow constraint. The accuracy of the method relies more heavily on the relative weighting of the smoothness and divergence-free constraints. In our experiments, the best results were obtained for a largely predominant divergence-free constraint. The results also show that the accuracy of the method is reasonable for low values of the rotation angle (minimum mean error of 1.1 voxel for 5 degrees). This is compatible with values reported in other studies for the overall rotation of the LV. We provide a qualitative description of the results obtained in vivo on a canine heart by visualizing the distribution of the estimated velocity vector magnitudes over the endocardial surface. These results (evolution of the field over time, maximum velocities) are in agreement with the known physiological behaviour of the heart.

Model extraction from magnetic resonance volume data using the deformable pyramid.

A general framework for automatic model extraction from magnetic resonance (MR) images is described. The framework is based on a two-stage algorithm. In the first stage, a geometrical and topological multiresolution prior model is constructed. It is based on a pyramid of graphs. In the second stage, a matching algorithm is described. This algorithm is used to deform the prior pyramid in a constrained manner. The topological and the main geometrical properties of the model are preserved, and at the same time, the model adapts itself to the input data. We show that it performs a fast and robust model extraction from image data containing unstructured information and noise. The efficiency of the deformable pyramid is illustrated on a synthetic image. Several examples of the method applied to MR volumes are also represented.

Two-dimensional spatial and temporal displacement and deformation field fitting from cardiac magnetic resonance tagging.

Tagged magnetic resonance imaging is a specially developed technique to noninvasively assess contractile function of the heart. Several methods have been developed to estimate myocardial deformation from tagged image data. Most of these methods do not explicitly impose a continuity constraint through time although myocardial motion is a continuous physical phenomenon. In this paper, we propose to model the spatio-temporal myocardial displacement field by a cosine series model fitted to the entire tagged dataset. The method has been implemented in two dimensions (2D)+time. Its accuracy was successively evaluated on actual tagged data and on a simulated two-dimensional (2D) moving heart model. The simulations show that an overall theoretical mean accuracy of 0.1 mm can be attained with adequate model orders. The influence of the tagging pattern was evaluated and computing time is provided as a function of the model complexity and data size. This method provides an analytical and hierarchical model of the 2D+time deformation inside the myocardium. It was applied to actual tagged data from a healthy subject and from a patient with ischemia. The results demonstrate the adequacy of the proposed model for this evaluation.

Simulated annealing, acceleration techniques, and image restoration.

Typically, the linear image restoration problem is an ill-conditioned, underdetermined inverse problem. Here, stabilization is achieved via the introduction of a first-order smoothness constraint which allows the preservation of edges and leads to the minimization of a nonconvex functional. In order to carry through this optimization task, we use stochastic relaxation with annealing. We prefer the Metropolis dynamics to the popular, but computationally much more expensive, Gibbs sampler. Still, Metropolis-type annealing algorithms are also widely reported to exhibit a low convergence rate. Their finite-time behavior is outlined and we investigate some inexpensive acceleration techniques that do not alter their theoretical convergence properties; namely, restriction of the state space to a locally bounded image space and increasing concave transform of the cost functional. Successful experiments about space-variant restoration of simulated synthetic aperture imaging data illustrate the performance of the resulting class of algorithms and show significant benefits in terms of convergence speed.

Assessment and visualization of the curvature of the left ventricle from 3D medical images.

We address the problem of using curvature features to assess the three-dimensional (3D) motion of the left ventricle. The adequacy of this approach depends on the actual characteristics of the curvature of the left ventricle and particularly on the spatial and temporal stability of these features. From experimental data, we compute the distribution of the Gaussian curvature over the surface of the left ventricle by using an iterative procedure. The results are visualized in 3D through a voxel-based surface rendering technique. We show that the Gaussian curvature remains stable along the cardiac cycle. This curvature feature could thus provide a reliable basis for further 3D motion analysis of the left ventricle.

Image quality study in 3D X-ray angiography: a first approach using the experimental design strategy.

The visual detection of fine structures and the accuracy of the quantitation of geometric and densitometric features, are closely related to the quality of the images available in two-dimensional (2D) and three-dimensional (3D) X-ray angiography. In this context, we propose to analyze all the parameters influencing this accuracy using an experimental design strategy. Preliminary tests of this procedure, applied to 2D and 3D angiographic data obtained from a dedicated phantom, yield encouraging results. We show that the detection of small arteries in a 3D angiogram is more sensitive to the number of projections than to the X-ray dose.

A new fully-digital anthropomorphic and dynamic thorax/heart model.

A numerical anthropomorphic model of the breathing thorax and the beating heart is presented. It includes the main thoracic/cardiac anatomical structures, the main vessel junctions as well as the structures' motion. Its main feature is that it is based on a Magnetic Resonance Imaging (MRI) examination performed on the same human subject within the same session from which both structural and motion information are retrieved. This confers to the model a very good consistency. This numerical model is virtually imaged by two simulators: a MRI simulator and a Positron Emission Tomography (PET) simulator. The overall resulting model (structure geometry & dynamics, images) is useful for the evaluation of cardiac image processing algorithms such as heart structure segmentation or multi-modality cardiac image registration.

Grid-enabling medical image analysis.

Grids have emerged as a promising technology to handle the data and compute intensive requirements of many application areas. Digital medical image processing is a promising application area for grids. Given the volume of data, the sensitivity of medical information, and the joint complexity of medical datasets and computations expected in clinical practice, the challenge is to fill the gap between the grid middleware and the requirements of clinical applications. The research project AGIR (Grid Analysis of Radiological Data) presented in this paper addresses this challenge through a combined approach: on one hand, leveraging the grid middleware through core grid medical services which target the requirements of medical data processing applications; on the other hand, grid-enabling a panel of applications ranging from algorithmic research to clinical applications.

Stereoscopic visualization of three-dimensional ultrasonic data applied to breast tumours.

OBJECTIVE: This paper presents a technique for stereoscopic visualization applied to three-dimensional (3D) ultrasonic breast data. METHODS: A motorized acquisition system has been designed to translate regularly a linear-phased array transducer, in order to provide a series of parallel echographic slices of the breast. During acquisition, the breast is compressed between a plane support and a plexiglass plate to avoid breast motion. A window in this plate provides access for ultrasonic exploration. From the series of cross-sectional scans, a 3D volume is formed by interpolation between the successive ultrasonic images. A stereoscopic computer-graphic method has been developed to visualize these 3D ultrasonic data. Two conical transparent projections of the volume are computed from two slightly different viewpoints. These two projections make up the stereoscopic pair. This pair is displayed on a stereoscopic monitor for the visualization of the 3D data with the depth dimension. RESULTS: The acquisition system and the method for computing the stereo-echograms were validated using an agar gel phantom. In vivo breast experiments were also performed. CONCLUSION: Visualization of stereo-echographic projections improves the perception of depth and shape of breast tumours.