Dominique Zosso

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In this paper we present a novel geometric framework called geodesic active fields for general image registration. In image registration, one looks for the underlying deformation field that best maps one image onto another. This is a classic ill-posed inverse problem, which is usually solved by adding a regularization term. Here, we propose a multiplicative(More)
We propose a segmentation method based on the geometric representation of images as 2-D manifolds embedded in a higher dimensional space. The segmentation is formulated as a minimization problem, where the contours are described by a level set function and the objective functional corresponds to the surface of the image manifold. In this geometric(More)
In this paper, we present a unifying framework for retinex that is able to reproduce many of the existing retinex implementations within a single model. The fundamental assumption, as shared with many retinex models, is that the observed image is a multiplication between the illumination and the true underlying reflectance of the object. Starting from(More)
The level set method is a popular technique for tracking moving interfaces in several disciplines, including computer vision and fluid dynamics. However, despite its high flexibility, the original level set method is limited by two important numerical issues. First, the level set method does not implicitly preserve the level set function as a distance(More)
—In this paper we define a scale-space for cortical mean curvature maps on the sphere, that offers a hierarchical representation of the brain cortical structures, useful in multiscale registration and analysis algorithms. A spherical feature map was obtained through inflation of the cortical surface of one hemisphere, extracted from structural MR images.(More)
Transcranial magnetic stimulation (TMS) is a well-known technique to study brain function. Location of TMS points can be visualized on the subject's Magnetic Resonance Image (MRI). However inter-subject comparison is possible only after a normalization i.e. a transformation of the stimulation points to a reference atlas image. Here, we propose a generic and(More)
We present a method to grid-enable tandem mass spectrometry protein identification. The implemented parallelization strategy embeds the open-source x!tandem tool in a grid-enabled workflow. This allows rapid analysis of large-scale mass spectrometry experiments on existing heterogeneous hardware. We have explored different data-splitting schemes,(More)