[Phot. d'atlas de Blaeu rangés dans leur armoire d'origine, du catalogue n°1397 de Frederik Muller, phot. offerte par ce dernier au prince R. Bonaparte le 6 mai 1896]

Donateur : Bonaparte, Roland (1858-1924)

Intervention of carbonate components in petrogenesis of the pyroxene nephelinites from the Jbel Saghro (Anti-Atlas, Morocco)

The Jbel Saghro alkaline complex was emplaced close to the eastern edge of the Moroccan Anti-Atlas. Within the northern part, two types of nephelinite were recognized [Ibhi and Nachit, 1999 and lbhi, 2000]. The first type (olivine-rich nephelinite) constitutes the main volcanic mass south of the Bou Gafer granit (fig. 1), where the volcanism had been active at least during 2 Ma, between 9.6 and 7.5 +/- 0.1 Ma [Berrahma et al., 1993]. The second group outcrops in the north (Foum El Kouss). It consists of pyroxene nephelinites which are younger (2.9 +/- 0.1 Ma) [Berrahma et al., 1993], and bears carbonatitic xenoliths, melteigitic pyroxenites and metasomatised peridotite xenoliths. Geochemically, the pyroxene nephelinite is highly enriched in LILE compared with the first one. The mineralogical and geochemical characteristics may be explained by the incorporation of carbonatitic and melteigitic pyroxenite segregates of carbonatitic affinity.

An active contour-based atlas registration model applied to automatic subthalamic nucleus targeting on MRI: method and validation.

This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.

Active Contour-Based Segmentation of Head and Neck with Adaptive Atlas Selection

This paper presents automated segmentation of structuresin the Head and Neck (H\&N) region, using an activecontour-based joint registration and segmentation model.A new atlas selection strategy is also used. Segmentationis performed based on the dense deformation fieldcomputed from the registration of selected structures inthe atlas image that have distinct boundaries, onto thepatient's image. This approach results in robustsegmentation of the structures of interest, even in thepresence of tumors, or anatomical differences between theatlas and the patient image. For each patient, an atlasimage is selected from the available atlas-database,based on the similarity metric value, computed afterperforming an affine registration between each image inthe atlas-database and the patient's image. Unlike manyof the previous approaches in the literature, thesimilarity metric is not computed over the entire imageregion; rather, it is computed only in the regions ofsoft tissue structures to be segmented. Qualitative andquantitative evaluation of the results is presented.

Au coeur de l'Atlas, mission au Maroc, 1904-1905. Préfaces de M. Eugène Étienne,... et du général Lyautey,... Note de géologie et de géographie physique, par M. Louis Gentil...

Comprend : Préface ; Note de géologie et de géographie physique ; Préface

Segmentation of Head and Neck Lymph Node Regions for Radiotherapy Planning Using Active Contour-Based Atlas Registration

In this paper, we present the segmentation of the headand neck lymph node regions using a new active contourbased atlas registration model. We propose to segment thelymph node regions without directly including them in theatlas registration process; instead, they are segmentedusing the dense deformation field computed from theregistration of the atlas structures with distinctboundaries. This approach results in robust and accuratesegmentation of the lymph node regions even in thepresence of significant anatomical variations between theatlas-image and the patient's image to be segmented. Wealso present a quantitative evaluation of lymph noderegions segmentation using various statistical as well asgeometrical metrics: sensitivity, specificity, dicesimilarity coefficient and Hausdorff distance. Acomparison of the proposed method with two other state ofthe art methods is presented. The robustness of theproposed method to the atlas selection, in segmenting thelymph node regions, is also evaluated.