Attribute Controlled Reconstruction and Adaptive Mathematical Morphology

ISBN : 978-3-642-38293-2International audienceIn this paper we present a reconstruction method controlled by the evolution of attributes. The process begins from a marker, propagated over increasing quasi-flat zones. The evolution of several increasing and non-increasing attributes is studied in order to select the appropriate region. Additionally, the combination of attributes can be used in a straightforward way. To demonstrate the performance of our method, three applications are presented. Firstly, our method successfully segments connected objects in range images. Secondly, input-adaptive structuring elements (SE) are defined computing the controlled propagation for each pixel on a pilot image. Finally, input-adaptive SE are used to assess shape features on the image. Our approach is multi-scale and auto-dual. Compared with other methods, it is based on a given attribute but does not require a size parameter in order to determine appropriate regions. It is useful to extract objects of a given shape. Additionally, our reconstruction is a connected operator since quasi-flat zones do not create new contours on the image

Conditional Sampling for Max-Stable Processes with a Mixed Moving Maxima Representation

This paper deals with the question of conditional sampling and prediction for the class of stationary max-stable processes which allow for a mixed moving maxima representation. We develop an exact procedure for conditional sampling using the Poisson point process structure of such processes. For explicit calculations we restrict ourselves to the one-dimensional case and use a finite number of shape functions satisfying some regularity conditions. For more general shape functions approximation techniques are presented. Our algorithm is applied to the Smith process and the Brown-Resnick process. Finally, we compare our computational results to other approaches. Here, the algorithm for Gaussian processes with transformed marginals turns out to be surprisingly competitive.Comment: 35 pages; version accepted for publication in Extremes. The final publication is available at http://link.springer.co

Lithofacies uncertainty modeling in a siliciclastic reservoir setting by incorporating geological contacts and seismic information

Deterministic modeling lonely provides a unique boundary layout, depending on the geological interpretation or interpolation from the hard available data. Changing the interpreter’s attitude or interpolation parameters leads to displacing the location of these borders. In contrary, probabilistic modeling of geological domains such as lithofacies is a critical aspect to providing information to take proper decision in the case of evaluation of oil reservoirs parameters, that is, applicable for quantification of uncertainty along the boundaries. These stochastic modeling manifests itself dramatically beyond this occasion. Conventional approaches of probabilistic modeling (object and pixel-based) mostly suffers from consideration of contact knowledge on the simulated domains. Plurigaussian simulation algorithm, in contrast, allows reproducing the complex transitions among the lithofacies domains and has found wide acceptance for modeling petroleum reservoirs. Stationary assumption for this framework has implications on the homogeneous characterization of the lithofacies. In this case, the proportion is assumed constant and the covariance function as a typical feature of spatial continuity depends only on the Euclidean distances between two points. But, whenever there exists a heterogeneity phenomenon in the region, this assumption does not urge model to generate the desired variability of the underlying proportion of facies over the domain. Geophysical attributes as a secondary variable in this place, plays an important role for generation of the realistic contact relationship between the simulated categories. In this paper, a hierarchical plurigaussian simulation approach is used to construct multiple realizations of lithofacies by incorporating the acoustic impedance as soft data through an oil reservoir in Iran.This research was funded by the National Elites Foundation of Iran in collaboration with research Institute Petroleum of Industry in Iran under the project number of 9265005

Computational Homogenization of Architectured Materials

Architectured materials involve geometrically engineered distributions of microstructural phases at a scale comparable to the scale of the component, thus calling for new models in order to determine the effective properties of materials. The present chapter aims at providing such models, in the case of mechanical properties. As a matter of fact, one engineering challenge is to predict the effective properties of such materials; computational homogenization using finite element analysis is a powerful tool to do so. Homogenized behavior of architectured materials can thus be used in large structural computations, hence enabling the dissemination of architectured materials in the industry. Furthermore, computational homogenization is the basis for computational topology optimization which will give rise to the next generation of architectured materials. This chapter covers the computational homogenization of periodic architectured materials in elasticity and plasticity, as well as the homogenization and representativity of random architectured materials

Noncanonical GLI1 signaling promotes stemness features and in vivo growth in lung adenocarcinoma

Aberrant Hedgehog/GLI signaling has been implicated in a diverse spectrum of human cancers, but its role in lung adenocarcinoma (LAC) is still under debate. We show that the downstream effector of the Hedgehog pathway, GLI1, is expressed in 76% of LACs, but in roughly half of these tumors, the canonical pathway activator, Smoothened, is expressed at low levels, possibly owing to epigenetic silencing. In LAC cells including the cancer stem cell compartment, we show that GLI1 is activated noncanonically by MAPK/ERK signaling. Different mechanisms can trigger the MAPK/ERK/GLI1 cascade including KRAS mutation and stimulation of NRP2 by VEGF produced by the cancer cells themselves in an autocrine loop or by stromal cells as paracrine cross talk. Suppression of GLI1, by silencing or drug-mediated, inhibits LAC cells proliferation, attenuates their stemness and increases their susceptibility to apoptosis in vitro and in vivo. These findings provide insight into the growth of LACs and point to GLI1 as a downstream effector for oncogenic pathways. Thus, strategies involving direct inhibition of GLI1 may be useful in the treatment of LACs

Alterations of Rb pathway (Rb-p16INK4-cyclin D1) in preinvasive bronchial lesions.

International audienceLung cancer results from a stepwise accumulation of genetic and molecular abnormalities with unknown temporal relationships to precursor bronchial lesions. In a search for biomarkers of malignant progression, we analyzed the expression of the tumor suppressor gene Rb and of the proteins regulating its phosphorylation and function in G1 arrest, p16INK4A and cyclin D1, in preinvasive bronchial lesions accompanying cancer in 75 patients, in comparison with similar lesions in 22 patients with no cancer history. Rb was constantly expressed in preinvasive lesions, including carcinoma in situ (CIS). In contrast, p16 expression was lost in moderate dysplasia (12%) and in CIS (30%) in patients with lung cancer. p16 loss occurred exclusively in patients who displayed loss of p16 expression in their related invasive carcinoma. Loss of p16 expression was not seen in nine patients with dysplasia but no cancer progression. Cyclin D1 overexpression was seen in hyperplasia and metaplasia (6%), mild dysplasia (17%), moderate dysplasia (46%), and CIS (38%) in patients with cancer but was lost in 5% of the patients during the process of invasion; it was also observed in patients with no cancer progression (14%). Our results indicate that Rb protein function can be invalidated before invasion through alteration of the Rb phosphorylation pathway, by p16 inhibition, and/or by cyclin D1 overexpression and suggest a role for p16 and cyclin D1 deregulation in progression of preinvasive bronchial lesions to invasive carcinoma