Dimitri Papadopoulos-Orfanos

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This paper describes a decade-long research program focused on the variability of the cortical folding patterns. The program has developed a framework of using artificial neuroanatomists that are trained to identify sulci from a database. The framework relies on a renormalization of the brain warping problem, which consists in matching the cortices at the(More)
This paper describes a complete system allowing automatic recognition of the main sulci of the human cortex. This system relies on a preprocessing of magnetic resonance images leading to abstract structural representations of the cortical folding patterns. The representation nodes are cortical folds, which are given a sulcus name by a contextual pattern(More)
Most of the approaches dedicated to automatic morphometry rely on a point-by-point strategy based on warping each brain toward a reference coordinate system. In this paper, we describe an alternative object-based strategy dedicated to the cortex. This strategy relies on an artificial neuroanatomist performing automatic recognition of the main cortical sulci(More)
In this paper we propose a generic automatic approach for the parcellation of the cortical surface into labeled gyri. These gyri are defined from a set of pairs of sulci selected by the user. The selected sulci are first automatically identified in the data, then projected onto the cortical surface. The parcellation stems from two nested Voronoï diagrams(More)
In this article we merge point feature and intensity-based registration in a single algorithm to tackle the problem of multiple brain registration. Because of the high variability of the shape of the cortex across individuals, there exist geometrical ambiguities in the registration process that an intensity measure alone is unable to solve. This problem can(More)
We describe here a classification system based on automatically identified cortical sulci. Multivariate recognition methods are required for the detection of complex brain patterns with a spatial distribution. However, such methods may face the well-known issue of the curse of dimensionality-the risk of overfitting the training dataset in high-dimensional(More)
We address the problem of the automation of surface digitization using a precision 3-0 laser rangejnde Because of their small field of view, such sensors navigate closely to the digitized object and are subject to collisions. Unlike previous techniques that addressed only the exhaustiveness of digitization, this work focuses on collision avoidance. To(More)
A family of methods aiming at the reconstruction of a putative fascicle map from any diffusion-weighted dataset is proposed. This fascicle map is defined as a trade-off between local information on voxel microstructure provided by diffusion data and a priori information on the low curvature of plausible fascicles. The optimal fascicle map is the minimum(More)
In this paper, we propose a new representation of the cortical surface that may be used to study the cortex folding process and to recover foetus sulcal roots usually burried in the depth of adult brains. This representation is a primal sketch derived from a scale space computed for the mean curvature of the cortical surface. This scale-space stems from a(More)
In this paper, we propose a generic automatic approach for the parcellation of the cortical surface into labelled gyri. These gyri are defined from a set of pairs of sulci selected by the user. The selected sulci are first automatically identified in the data, then projected onto the cortical surface. The parcellation stems from two nested Voronoı̈ diagrams(More)