Curing coronary artery disease typically involves deploying a stent (a fine mesh of wire) supported by a balloon inside the patient artery. This procedure is monitored by X-ray fluoroscopy where stent visibility is challenging. Since 2000, stent enhancement techniques for X-ray fluoroscopy image sequences have become popular. They are based on motion compensated temporal integration of the stent images. The motion of the stent is classically inferred from the motion of the highly contrasted balloon marker balls. We propose a technique that compensates the motion of the whole guide-wire in the neighborhood of the marker balls. We demonstrate that the guide wire-based registration enables better enhanced images in 28% of the cases whereas marker ball based registration is better only in 4% of the cases. We provide examples, qualitative and quantitative analysis on a database of 144 clinical cases.

In X-ray interventional imaging, improved denoising enables lower X-ray dose and better visualization, resulting in increased confidence in the therapeutic act. This article focuses on the denoising of fluoroscopic image sequences in interventional cardiology. The challenge with these images is the need to preserve fine details in terms of size and contrast, representing the tools manipulated by the operator. These tools superimpose over an anatomical background. This context drives us to propose an algorithm based on spatial-temporal filtering conditioned by a feature of interest map. Based on the confidence in the feature detection our algorithm will either filter, preserve or enhance the image content. Our method is fast and compares very favorably with state of the art methods both quantitatively on synthetic data and perceptually on clinical data.

This paper presents a new method for 3-D tomographic reconstruction of stent in X-ray cardiac rotational angiography. The method relies on 2-D motion correction from two radiopaque markerballs located on each side of the stent. The two markerballs are on a guidewire and linked to the balloon, which is introduced into the artery. Once the balloon has been inflated, deflated, and the stent deployed, a rotational sequence around the patient is acquired. Under the assumption that the guidewire and the stent have the same 3-D motion during rotational acquisition, we developed an algorithm to correct cardiac stent motion on the 2-D X-ray projection images. The 3-D image of the deployed stent is then reconstructed with the Feldkamp algorithm using all the available projections. Although the correction is an approximation, we show that the intrinsic geometrical error of our method has no visual impact on the reconstruction when the 2-D markerball centers are exactly detected and the markerballs have the same 3-D motion as the stent. Qualitative and quantitative results on simulated sequences under different realistic conditions demonstrate the robustness of the method. Finally, results from animal data acquired on a rotational angiography device are presented.

Cardiovascular diseases remain the primary cause of death in developed countries. In most cases, exploration of possibly underlying coronary artery pathologies is performed using X-ray coronary angiography. Current clinical routine in coronary angiography is directly conducted in two-dimensional projection images from several static viewing angles. However, for diagnosis and treatment purposes, coronary artery reconstruction is highly suitable. The purpose of this study is to provide physicians with a three-dimensional (3-D) model of coronary arteries, e.g., for absolute 3-D measures for lesion assessment, instead of direct projective measures deduced from the images, which are highly dependent on the viewing angle. In this paper, we propose a novel method to reconstruct coronary arteries from one single rotational X-ray projection sequence. As a side result, we also obtain an estimation of the coronary artery motion. Our method consists of three main consecutive steps: 1) 3-D reconstruction of coronary artery centerlines, including respiratory motion compensation; 2) coronary artery four-dimensional motion computation; 3) 3-D tomographic reconstruction of coronary arteries, involving compensation for respiratory and cardiac motions. We present some experiments on clinical datasets, and the feasibility of a true 3-D Quantitative Coronary Analysis is demonstrated.

We propose to identify particular shapes of an image surface a method based on the fuzzy analysis of the eigen values space. We have used the framework of differential geometry, and used a multilocal analysis. We have integrated this method into a medical application.

In this paper, we present a new approach to segment vessels from 3D angiography of the brain. Our approach is based on a vessel model and uses a multiscale analysis in order to extract the vessel network surrounding an aneurysm. Our model allows us to choose a criterion based on the eigenvalues of the Hessian matrix for selecting a subset of interesting points near the vessel center. It also allows us to choose a good parameter for a /spl gamma/-normalization of the single scale response. The response at one scale is obtained by integrating along a circle the first derivative of the intensity in the radial direction. Once the multiscale response is obtained, we create a smoothed skeleton of the vessels combined with a MIP or a volume rendering to enhance their visualization. The method has been tested on a large variety of 3-D images of the brain, with excellent results. Vessels of various size and contrast are detected with a remarkable robustness, and most junctions are preserved.

The extremal boundaries, of 3-D curved objects are the images of special curves drawn on the object and are called rims. They are viewpoint dependent and characterized by the fact that the optical rays of their points are tangential to the surface of the object. The mathematics of the relationship between the extremal boundaries and the surface of the object is studied. This study makes it possible to design an algorithm for detecting those boundaries in the images that are likely to be extremal. Once this has been done, one can reconstruct the rims and compute the differential properties of the surface of the object along them up to the second order. If a qualitative description is sufficient, the sign of the Gaussian curvature of the surface along the rim can be computed in a much simpler way. Experimental results are presented on synthetic and real images. The work provides a better understanding of the relationship between the apparent and real shape of a 3-D object as well as algorithms for reconstructing the local shape of such an object along the rims.>