Showing papers by "Nicholas Ayache published in 1997"

Directional Anisotropic Diffusion Applied to Segmentation of Vessels in 3D Images

Abstract: Anisotropic diffusion is a method which allows to reduce the noise in the image without blurring the frontiers between different regions. This process can be applied in medical image analysis to segment the different anatomical structures. In this article, we introduce a new implementation of the anisotropic diffusion which better preserves small structures like vessels in 3D images. This method is based on the explicit weighting of the diffusion in the directions of the gradient, and minimum and maximum curvatures. This algorithm gave good results on real medical images.

Matching 3D MR angiography data and 2D X-ray angiograms

Abstract: In this paper we present a new algorithm for matching a 3D MR angiography volume image with two 2D X-ray angiograms without using artificial markers. The goal is to prove the feasibility of such a technique, and the long-term aim is to be able to report the catheter position in a 3D pre-operative image, during an X-ray angiographic examination. First, vessels centerlines are computed using a novel algorithm. Then matching is performed using an extension of the ICP algorithm. Special care is taken in dealing with outliers. Comparing the results on real data of our algorithm with a stereotactic frame-based registration, the accuracy of our method is proved to be better than 2 mm in the worse case with good repeatability. This makes it usable for clinical applications.

Definition of a 4D continuous polar transformation for the tracking and the analysis of LV motion

Abstract: A 4D polar transformation is defined to describe the left ventricle (LV) motion and a method is presented to estimate it from sequences of 3D images. The transformation is defined in 3D-planispheric coordinates by a small number of parameters involved in a set of simple linear equations. It is continuous and regular in time and space, periodicity in time can be imposed. The local motion can be easily decomposed into a few canonical motions (centripetal contraction, rotation around the long-axis, elevation). To recover the motion from original data, the 4D polar transformation is calculated using an adaptation of the Iterative Closest Point algorithm. We present the mathematical framework and a demonstration of its feasability on a gated SPECT sequence.

Electronic image processing device for the detection of motions

Abstract: An electronic processing device receives sets of image data representing respectively sequential three-dimensional digital images of the same region. This device comprises means capable of defining a three-dimensional shape of interest on the basis of at least one of the sets of image data, and of extracting from each set image data representing characteristic points of the shape of interest, processing means for establishing on the basis of the image data of the contours a spatial-temporal planispheric transformation making it possible to pass from characteristic points extracted from one image to the characteristic points extracted from another image of the sequence, and means for displaying selected motion data derived from the parameters of the transformation.

Medical Image Analysis and Simulation

Abstract: This article introduces the research field of digital image analysis and simulation applied to medicine

[A new concept in digestive surgery: the computer assisted surgical procedure, from virtual reality to telemanipulation].

Abstract: Surgical simulation increasingly appears to be an essential aspect of tomorrow's surgery. The development of a hepatic surgery simulator is an advanced concept calling for a new writing system which will transform the medical world: virtual reality. Virtual reality extends the perception of our five senses by representing more than the real state of things by the means of computer sciences and robotics. It consists of three concepts: immersion, navigation and interaction. Three reasons have led us to develop this simulator: the first is to provide the surgeon with a comprehensive visualisation of the organ. The second reason is to allow for planning and surgical simulation that could be compared with the detailed flight-plan for a commercial jet pilot. The third lies in the fact that virtual reality is an integrated part of the concept of computer assisted surgical procedure. The project consists of a sophisticated simulator which has to include five requirements: visual fidelity, interactivity, physical properties, physiological properties, sensory input and output. In this report we will describe how to get a realistic 3D model of the liver from bi-dimensional 2D medical images for anatomical and surgical training. The introduction of a tumor and the consequent planning and virtual resection is also described, as are force feedback and real-time interaction.

X-Ray Angiography in Stereotactic Conditions: Techniques and Interest for Interventional Neuroradiology

Abstract: This paper reports work in progress on X-ray angiography acquired under stereotactic conditions. The objective is to be able to match multimodality images (typically MRI and X-ray) without a stereotactic frame but with stereotactic precision. We have identified potential problems and have studied them in detail. We conclude that, although the overall application is feasible, much work remains to be done on the estimation of the X-ray system conic projection and on automatic matching based on vascular structures.

Electronic processing of image data to simulate deformation of object

Abstract: The electronic processing unit has a force generator (4) reacting to movement of a surgical tool, a collision module estimating the intersection between the tool and a given surface and an internal force module (16) that establishes internal forces in response to applied forces implied by surface deformation. The reaction forces are then computed to balance these internal forces.

Model-Based Multiscale Detection of 3D Vessels

Abstract: Presents a new approach to segment vessels from 3D angiography of the brain. The authors' approach is based on a vessel model and uses a multiscale analysis in order to extract the vessel network surrounding an aneurysm. The authors' model allows them 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 them 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, the authors 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.

Automatic Segmentation of Portal Vein in CT-Scans of the Liver

Abstract: Introduction We present a new automatic method to segment the portal vein in D helical CTs of the liver at portal time The purpose is to segment this vein with enough branchings and topological information to localize hepatic tumors with respect to Couinaud s anatomical segmentation Materials and Methods After detecting the liver contours using D deformable models we limit the initial CT images to a mask of liver that contains hepatic tissue vascular trees and possibly tumors To classify these anatomical structures we t three Gaussian curves to the intensity histogram using a least squares method We then segment vascular trees and tumors by applying a new hysteresis thresholding technique based on a distance map and the thresholds computed from the Gaussian parameters The resulting vascular system is improved in order to deal with the anisotropy of images and the textured aspect of liver First to obtain an isotropic image we perform a shape based interpolation on