Gif-sur-Yvette, France
Gif-sur-Yvette, France

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Guevara P.,CEA Saclay Nuclear Research Center | Guevara P.,Institute Federatif Of Recherche 49 | Guevara P.,University of Concepción | Duclap D.,CEA Saclay Nuclear Research Center | And 11 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2011

This paper presents a method for automatic segmentation of some short association fiber bundles from massive dMRI tractography datasets. The method is based on a multi-subject bundle atlas derived from a two-level intra-subject and inter-subject clustering strategy. Each atlas bundle corresponds to one or more inter-subject clusters, presenting similar shapes. An atlas bundle is represented by the multi-subject list of the centroids of all intra-subject clusters in order to get a good sampling of the shape and localization variability. An atlas of 47 bundles is inferred from a first database of 12 brains, and used to segment the same bundles in a second database of 10 brains. © 2011 Springer-Verlag.


Marrakchi-Kacem L.,CEA Saclay Nuclear Research Center | Marrakchi-Kacem L.,Institute Federatif Of Recherche 49 | Delmaire C.,Institute Federatif Of Recherche 49 | Delmaire C.,Pitie Salpetriere Hospital | And 17 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2010

The deep brain nuclei play an important role in many brain functions and particularly motor control. Damage to these structures result in movement disorders such as in Parkinson's disease or Huntington's disease, or behavioural disorders such as Tourette syndrome. In this paper, we propose to study the connectivity profile of the deep nuclei to the motor, associative or limbic areas and we introduce a novel tool to build a probabilistic atlas of these connections to the cortex directly on the surface of the cortical mantel, as it corresponds to the space of functional interest. The tool is then applied on two populations of healthy volunteers and patients suffering from severe Huntington's disease to produce two surface atlases of the connectivity of the basal ganglia to the cortical areas. Finally, robust statistics are used to characterize the differences of that connectivity between the two populations, providing new connectivity-based biomarkers of the pathology. © 2010 Springer-Verlag.


Guevara P.,CEA Saclay Nuclear Research Center | Guevara P.,Institute Federatif Of Recherche 49 | Poupon C.,CEA Saclay Nuclear Research Center | Poupon C.,Institute Federatif Of Recherche 49 | And 15 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2010

This paper presents a method inferring a model of the brain white matter organisation from HARDI tractography results computed for a group of subjects. This model is made up of a set of generic fiber bundles that can be detected in most of the population. Our approach is based on a two-level clustering strategy. The first level is a multiresolution intra-subject clustering of the million tracts that are computed for each brain. This analysis reduces the complexity of the data to a few thousands fiber bundles for each subject. The second level is an inter-subject clustering over fiber bundle centroids from all the subjects using a pairwise distance computed after spatial normalization. The resulting model includes the large bundles of anatomical literature and about 20 U-fiber bundles in each hemisphere. © 2010 Springer-Verlag.


Roca P.,CEA Saclay Nuclear Research Center | Roca P.,Institute Federatif Of Recherche 49 | Tucholka A.,CEA Saclay Nuclear Research Center | Tucholka A.,Institute Federatif Of Recherche 49 | And 9 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2010

This paper presents a connectivity-based parcellation of the human post-central gyrus, at the level of the group of subjects. The dimension of the clustering problem is reduced using a set of cortical regions of interest determined at the inter-subject level using a surface-based coordinate system, and representing the regions with a strong connection to the post-central gyrus. This process allows a clustering based on criteria which are more reproducible across subjects than in an intra-subject approach. We obtained parcels relatively stable in localisation across subjects as well as homogenous and well-separated to each other in terms of connectivity profiles. To address the parcellation at the inter-subject level provides a direct matching between parcels across subjects. In addition, this method allows the identification of subject-specific parcels. This property could be useful for the study of pathologies. © 2010 Springer-Verlag.

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