Christine Graffigne

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We use a statistical framework for finding boundaries and for partitioning scenes into homogeneous regions. The model is a joint probability distribution for the a r ray of pixel gray levels and an a r ray of “labels.” In boundary finding, the labels a re binary, zero, or one, representing the absence o r presence of boundary elements. In partitioning, the(More)
1. Introduction. Computer vision refers to a variety of applications involving a sensing device, a computer, and software for restoring and possibly interpreting the sensed data. Most commonly, visible light is sensed by a video camera and converted to an array of measured light intensities, each element corresponding to a small patch in the scene (a(More)
The aim of this work is to track speciic anatomical structures in temporal sequences of echocardiographic images. Ultrasound images are available in two broad data types: raw or video data. Diierent stochastic processes using diierent kind of information are compared on the basis of these two data types. We explain the selection of a particular model w.r.t.(More)
One essential assumption used in object detection and labeling by imaging is that the photometric properties of the object are homogeneous. This homogeneousness requirement is often violated in microscopy imaging. Classical methods are usually of high computational cost and fail to give a stable solution. This paper presents a low computational complexity(More)
Iron overload is an ineluctable complication in chronically transfused children warranting accurate assessment to avoid related morbidity. We investigated longitudinally the relationships between ferritin levels and hepatic and cardiac T2* magnetic resonance imaging (MRI) in a cohort of chronically transfused children receiving chelation therapy. Thirty(More)
This paper explores a generic approach to predict the output accuracy of an algorithm without running it, by a careful examination of the local context. Such a performance prediction will allow one to qualify the appropriateness of an algorithm to treat images with given properties (contrast, resolution, noise, richness in details, contours or textures,(More)
This paper evaluates a K-Markov random field model for retrieving information about backscatter characteristics, especially regularity spacing scatterers in simulated ultrasound image. The model combines a statistical K-distribution that describes the envelope of backscattered echo and spatial interaction given by Markov random field (MRF). Parameters(More)