Atlas-manuel des maladies du larynx (2e éd.) / par le Dr L. Grünwald ; édition française par A. Castex,... P. Collinet,...

Collection : Atlas-manuels de médecine

Atlas sedimentológico de la plataforma continental peruana

Presenta un atlas sedimentológico compuesto por un texto explicativo y 19 cartas elaboradas en base a la información obtenida de 726 muestras de sedimento superficial de la plataforma continental peruana y del talud continental, extraídas entre 1976 y 1983 mediante una draga Van Veen de 0,10m2. Incluye la batimetría de la zona estudiada,la ubicación de los puntos de muestreo, la textura y granulometría del sedimento, así como el contenido tanto de carbonatos como de carbono orgánico. Las cartas son más detalladas para la plataforma que para el talud y muestran la predominancia de sedimentos arenosos en la mayor parte de la plataforma continental y del talud superior entre los 6°15' y 10°30' S, y la presencia de arcilla limosa cubriendo todo el talud continental y gran parte de la plataforma al sur de los 10°30' S. En cuanto al carbono orgánico y carbonatos se observa valores muy bajos ( <2% de carbono orgánico y <10% de carbonatos en sedimento) al norte de los 10"30'S y valores altos (>5%- 20% de carbono orgánico y hasta de 30%-50% de carbonatos) al sur de los 10°30'S.

[Trois feuilles d'un atlas géologique ou destinées à un ouvrage de géologie] / Lith. P. Bineteau

Échelle(s) : Échelle indéterminable

Atlas del Instituto del Mar del Perú

Atlas de información general sobre el Instituto del Mar del Perú sobre determinadas condiciones biológicas, físicas y químicas

Atlas-based segmentation of pathological MR brain images using a model of lesion growth.

We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.

Dense deformation field estimation for atlas-based segmentation of pathological MR brain images.

Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.

A protein interaction atlas for the nuclear receptors: properties and quality of a hub-based dimerisation network.

BACKGROUND: The nuclear receptors are a large family of eukaryotic transcription factors that constitute major pharmacological targets. They exert their combinatorial control through homotypic heterodimerisation. Elucidation of this dimerisation network is vital in order to understand the complex dynamics and potential cross-talk involved. RESULTS: Phylogeny, protein-protein interactions, protein-DNA interactions and gene expression data have been integrated to provide a comprehensive and up-to-date description of the topology and properties of the nuclear receptor interaction network in humans. We discriminate between DNA-binding and non-DNA-binding dimers, and provide a comprehensive interaction map, that identifies potential cross-talk between the various pathways of nuclear receptors. CONCLUSION: We infer that the topology of this network is hub-based, and much more connected than previously thought. The hub-based topology of the network and the wide tissue expression pattern of NRs create a highly competitive environment for the common heterodimerising partners. Furthermore, a significant number of negative feedback loops is present, with the hub protein SHP [NR0B2] playing a major role. We also compare the evolution, topology and properties of the nuclear receptor network with the hub-based dimerisation network of the bHLH transcription factors in order to identify both unique themes and ubiquitous properties in gene regulation. In terms of methodology, we conclude that such a comprehensive picture can only be assembled by semi-automated text-mining, manual curation and integration of data from various sources.