Contours déformables et reconstruction tomographique en imagerie médicale

Cet article traite de la segmentation automatique des images reconstruites en tomographie par émission, afin d'améliorer l'interprétation des images pour le diagnostic des médecins. Les approches classiques des contours actifs déformables pour la segmentation ne permettent pas de bien segmenter les données reconstruites qui sont bruitées. Aussi, nous proposons de traiter simultanément la reconstruction et la segmentation en résolvant un système de deux EDP, l'une permettant la reconstruction avec régularisation prenant en compte les discontinuités, et l'autre la segmentation par l'évolution de courbes planes

Level Set Methods for Stochastic Discontinuity Detection in Nonlinear Problems

Stochastic physical problems governed by nonlinear conservation laws are challenging due to solution discontinuities in stochastic and physical space. In this paper, we present a level set method to track discontinuities in stochastic space by solving a Hamilton-Jacobi equation. By introducing a speed function that vanishes at discontinuities, the iso-zero of the level set problem coincide with the discontinuities of the conservation law. The level set problem is solved on a sequence of successively finer grids in stochastic space. The method is adaptive in the sense that costly evaluations of the conservation law of interest are only performed in the vicinity of the discontinuities during the refinement stage. In regions of stochastic space where the solution is smooth, a surrogate method replaces expensive evaluations of the conservation law. The proposed method is tested in conjunction with different sets of localized orthogonal basis functions on simplex elements, as well as frames based on piecewise polynomials conforming to the level set function. The performance of the proposed method is compared to existing adaptive multi-element generalized polynomial chaos methods

Color Image Segmentation by Voronoi Partitions

We address the issue of low-level segmentation of color images. The proposed approach is based on the formulation of the problem as a generalized Voronoi partition of the image domain. In this context, a segmentation is determined by the definition of a distance between points of the image and the selection of a set of sites. The distance is defined by considering the low-level attributes of the image and, particularly, the color information. We divide the segmentation task in three successive sub-tasks, treated in the framework of Voronoi partitions : pre-segmentation, hierarchical representation and contour extraction.Nous étudions le problème de la segmentation de bas niveau pour les images couleur. L'approche proposée consiste à modéliser la segmentation d'une image comme une partition de Voronoï généralisée de son domaine. Dans ce contexte, segmenter une image couleur revient à définir une distance appropriée entre points de l'image et à choisir un ensemble de sites. La distance est définie en considérant les attributs de bas niveau de l'image et, en particulier, l'information fournie par la couleur. La démarche adoptée repose sur la division du problème de la segmentation en trois sous-tâches successives, traitées dans le cadre des partitions de Voronoï : la pré-segmentation, la représentation hiérarchique et l'extraction de contours

Three dimensional flame reconstruction towards the study of fire-induced transmission line flashovers.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, 2007.The work presented in this thesis focuses on the problem of reconstructing threedimensional models of fire from real images. The intended application of the reconstructions is for use in research into the phenomenon of fire-induced high voltage flashover, which, while a common problem, is not fully understood. As such the reconstruction must estimate not only the geometry of the flame but also the internal density structure, using only a set of a few synchronised images. Current flame reconstruction techniques are investigated, revealing that relatively little work has been done on the subject, and that most techniques follow either an exclusively geometric or tomographic direction. A novel method, termed the 3D Fuzzy Hull method, is proposed, incorporating aspects of tomography, statistical image segmentation and traditional object reconstruction techniques. By using physically based principles the flame images are related to the relative flame density, allowing the problem to be tackled from a tomographic perspective. A variation of algebraic tomography is then used to estimate the internal density field of the flame. This is done within a geometric framework by integrating the fuzzy c-means image segmentation technique and the visual hull concept into the process. Results are presented using synthetic and real flame image sets

Level Set Methods for MRE Image Processing and Analysis

Ph.DDOCTOR OF PHILOSOPH

Development of Some Novel Nonlinear and Adaptive Digital Image Filters for Efficient Noise Suppression

Some nonlinear and adaptive digital image filtering algorithms have been developed in this thesis to suppress additive white Gaussian noise (AWGN), bipolar fixed-valued impulse, also called salt and pepper noise (SPN), random-valued impulse noise (RVIN) and their combinations quite effectively. The present state-of-art technology offers high quality sensors, cameras, electronic circuitry: application specific integrated circuits (ASIC), system on chip (SOC), etc., and high quality communication channels. Therefore, the noise level in images has been reduced drastically. In literature, many efficient nonlinear image filters are found that perform well under high noise conditions. But their performance is not so good under low noise conditions as compared to the extremely high computational complexity involved therein. Thus, it is felt that there is sufficient scope to investigate and develop quite efficient but simple algorithms to suppress low-power noise in an image. When..