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Accurate alignment of explicit surface representations of human cerebral cortices is necessary in order to compare local individual differences in cortical morphometric measurements (thickness, surface area, gyrification, etc.) in both normal and clinical populations. This paper presents a methodology for developing unbiased, high resolution iterative(More)
Some surfaces present folding patterns formed by juxtapositions of ridges and valleys as, for example, the cortical surface of the human brain. The fundamental problem with ridges is to find a correspondence among and analyze the variability among them. Many techniques to achieve these goals exist but use scalar functions. Depth maps are used to efficiently(More)
Popular online social networks (OSN) generate hundreds of terabytes of new data per day and connect millions of users. To help users cope with the immense scale and influx of new information, OSNs provide a search functionality. However, most of the search engines in OSNs today only support keyword queries and provide basic faceted search capabilities(More)
In magnetic resonance imaging based brain morphometry, Gaussian smoothing is often applied to increase the signal-to-noise ratio and to increase the detection power of statistical parametric maps. However, most existing studies used a single smoothing filter without adequately justifying their choices. In this article, we want to determine the extent for(More)
The folding pattern of the human cortical surface is organized in a coherent set of troughs and ridges, which mark important anatomical demarcations that are similar across subjects. Cortical surface shape is often analyzed in the literature using isotropic diffusion, a strategy that is questionable because many anatomical regions are known to follow the(More)
The cortical surface of the human brain is composed of folds that are juxtaposed alongside one another. Several methods have been proposed to study the shape of these folds, e.g., by first segmenting them on the cortical surface or by analysis via a continuous deformation of a common template. A major disadvantage of these methods is that, while they can(More)
<i>SLAM</i> is the generic name given to the class of methods allowing to incrementally build a 3D representation of an environment while simultaneously using this map to localize a mobile system evolving within this environment. Though quite a mature field, several scientific problems remain open and particularly the reduction of drift. Drift is inherent(More)
The variability of tensor fields is usually analyzed with multivariate statistical distributions. Multivariate distributions model every component of the tensor, which are not invariant under rotation. They therefore tell very little information about the true shape of the tensor. A statistical analysis on the eigenvalues of the tensor would be more(More)